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BULETINUL INSTITUTULUI POLITEHNIC DIN IAŞI Tomul LIX (LXIII)

Fasc. 1-2 TEXTILE. PIELĂRIE 2013 Editura POLITEHNIUM

BULETINUL INSTITUTULUI POLITEHNIC DIN IAŞI PUBLISHED BY

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Editorial Board

President: Prof. dr. eng. Ion Giurma, Member of the Academy of Agricultural Sciences and Forest, Rector of the “Gheorghe Asachi” Technical University of Iaşi

Editor-in-Chief: Prof. dr. eng. Carmen Teodosiu, Vice-Rector of the “Gheorghe Asachi” Technical University of Iaşi

Honorary Editors of the Bulletin: Prof. dr. eng. Alfred Braier, Prof. dr. eng. Hugo Rosman,

Prof. dr. eng. Mihail Voicu, Corresponding Member of the Romanian Academy

Editor in Chief of the TEXTILES. LEATHERSHIP Section Prof. dr. eng. Aurelia Grigoriu

Honorary Editors: Prof. dr. eng. Mihai Ciocoiu, Prof. dr. eng. Costache Rusu

Associated Editor: Lecturer dr. eng. LuminiŃa Ciobanu

Editorial Advisory Board

Prof.dr.eng. Mario de Araujo, University of Minho, Portugal

Prof.dr.eng. Vladan Koncar, National Highschool of Arts and Textile Industries of Roubaix, France

Prof.dr.eng. Silvia Avasilcăi, “Gheorghe Asachi” Technical University of Iaşi

Assoc.prof.dr.eng. Maria Carmen Loghin, “Gheorghe Asachi” Technical University of Iaşi

Prof.dr.eng. Pascal Bruniaux, National Highschool of Arts and Textile

Industries of Roubaix, France

Assoc.prof.dr.eng. Stelian-Sergiu Maier, “Gheorghe Asachi” Technical University

of Iaşi Prof.dr.eng. Ioan Cioară, “Gheorghe Asachi”

Technical University of Iaşi Prof.dr.eng. Jiri Militky, Technical University of Liberec, Chzeck Republik

Prof.dr.eng. M. Cetin Erdogan, EGE University of Izmir, Turkey

Prof.dr.eng. Augustin Mureşan, “Gheorghe Asachi” Technical University of Iaşi

Prof.dr.eng. Ana Marija Grancaric, University of Zagreb, CroaŃia

Prof.dr.eng. Crişan Popescu, DWI an der RTWH, Aachen University, Germany

Assoc.prof.dr.eng. Florentina Harnagea, “Gheorghe Asachi” Technical University of Iaşi

Dr.eng. Emilia Visileanu, CPI, INCDTP Bucureşti

Prof.dr.eng. Lubos Hes, Technical University of Liberec, Chzeck Republik

Assoc.prof.dr.eng. Mariana Ursache, “Gheorghe Asachi” Technical University of Iaşi

Prof.dr.eng. Huseyin Kadoglu, EGE University of Izmir, Turkey

Prof.dr.eng. Charles Yang, University of Georgia, Atlanta, USA

Prof.dr.eng. Paul Kiekens, University of Gent, Belgium

BULETINUL INSTITUTULUI POLITEHNIC DIN IAŞI BULLETIN OF THE POLYTECHNIC INSTITUTE OF IAŞI Tomul LIX (LXIII), Fasc. 1-2 2013

TEXTILE. PIELĂRIE

Pag.

DEMETRA LĂCRĂMIOARA BORDEIANU şi LILIANA HRISTIAN, Aspecte privind curăŃarea firelor simple şi răsucite tip bumbac (engl., rez. rom.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9

COSTICĂ SAVA şi MARIANA ICHIM, ProprietăŃile firelor filate cu rotor din amestec de in cotonizat şi bumbac (engl., rez. rom.) . . . . . . . . . . . . . . .

17

DOINA CAŞCAVAL, Model Markov redus pentru o problemă de interferenŃă a maşinilor de Ńesut (engl., rez. rom.) . . . . . . . . . . . . . . . . . . . . . . . . . .

25

IOAN CIOARĂ şi LUCICA CIOARĂ, Aspecte privind tensiunea statică a urzelii pe maşina de Ńesut (engl., rez. rom.) . . . . . . . . . . . . . . . . . . . . . . .

35

CRINA BUHAI şi MIRELA BLAGA, Compresia şi rigiditatea la încovoiere a tricoturilor din bătătură stratificate (engl., rez. rom.) . . . . . . . . . . . . . . .

43

EMILIA FILIPESCU, ELENA SPINACHI şi SABINA OLARU, Modelarea virtuală 3D – Tehnologie inovativă în simularea virtuală a corespondenŃei dintre corp şi produsul de îmbrăcăminte (engl., rez. rom.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

53

DANIELA NEGRU şi DORIN AVRAM, Materiale textile de încălzire peliculizate cu polipirol (engl., rez. rom.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

69

S U M A R

BULETINUL INSTITUTULUI POLITEHNIC DIN IAŞI BULLETIN OF THE POLYTECHNIC INSTITUTE OF IAŞI Tomul LIX (LXIII), Fasc. 1-2 2013

TEXTILES. LEATHERSHIP

Pp.

DEMETRA LĂCRĂMIOARA BORDEIANU and LILIANA HRISTIAN, Aspects Concerning the Cleaning of Simple and Twist Cotton-Type Yarns (English, Romanian summary) . . . . . . . . . . . . . . . . . . . . . . . . . .

9

COSTICĂ SAVA and MARIANA ICHIM, The properties of cottonised flax/cotton blended rotor spun yarns (English, Romanian summary) . . .

17

DOINA CAŞCAVAL, Reduced Markov Chain for a Weaving Machines Interference Problem (English, Romanian summary) . . . . . . . . . . . . . .

25

IOAN CIOARĂ and LUCICA CIOARĂ, Aspects Concerning the Warp Static Tension on Weaving Machine (English, Romanian summary) . . . . . . .

35

CRINA BUHAI and MIRELA BLAGA, Compression and Bending Stiffness of Functional Weft Knitted Fabrics (English, Romanian summary) . . . . . . .

43

EMILIA FILIPESCU, ELENA SPINACHI and SABINA OLARU, 3D Virtual Modeling - Innovative Technology to Simulate the Correspondence Between Body and Garment (English, Romanian summary) . . . . . . .

53 DANIELA NEGRU and DORIN AVRAM, Textile Heating Fabrics with

Polypyrrole Layer (English, Romanian summary) . . . . . . . . . . . . . . . . . 69

C O N T E N T S

BULETINUL INSTITUTULUI POLITEHNIC DIN IAŞI Publicat de

Universitatea Tehnică „Gheorghe Asachi” din Iaşi Tomul LIX (LXIII), Fasc. 1-2, 2013

SecŃia TEXTILE. PIELĂRIE

ASPECTS CONCERNING THE CLEANING OF SIMPLE AND TWIST COTTON-TYPE YARNS

BY

DEMETRA LĂCRĂMIOARA BORDEIANU and LILIANA HRISTIAN∗∗∗∗

“Gheorghe Asachi” Technical University of Iaşi,

Faculty of Textiles & Leather Engineering and Industrial Management

Received: February 27, 2013 Accepted for publication: April 5, 2013

Abstract. The work presents experimental results concerning the removal of rare flaws from cotton-type yarns by means of Leophe FR-30 electronic clearer installed on the Mettler spooler. The flaw frequency and shape allow identifying the cause-effect relationship at the level of the technological process which permits partial corrective actions; the elimination of damaging flaws whose appearance cannot be avoided, is performed by yarn cleaning in the spooling technological process. The presence of flaws (aggravated by the amplification of their frequency and shape) diminishes the processability of yarns and finally, the aspect of the woven and knitted fabrics produced from these yarns. The severity of yarns flaws is established based on the typo-dimensional criterion of classification, which permits establishing the values of the objective control limits. In order to appreciate the qualitative yarn level and the efficiency of cleaning operation, short section irregularities (U%), irregularities frequency within a 1000 m of yarn and the frequency of rare flaw/100 km of yarn before and after the cleaning operation have been analyzed for the following yarn assortment: yarn Nm 50/l (67% PES + 33% cotton); yarn Nm 70/l (67% cotton + 33% PES); yarn Nm 85/2 (67% PES + 33% cotton); yarn Nm 100/2 (67% PES + 33% cotton).

Key words: rare flaws, Classimat classification, cleaning, linear irregularity.

∗Corresponding author; e-mail: [email protected]

10 Demetra Lăcrămioara Bordeianu and Liliana Hristian

1. Introduction

Structural and aspect characteristics of the yarns, reflected in the number of rare damaging, short, intermediate and mainly long and thick flaws, influence to a great extent the quality and aspect of the woven or knitted fabrics.

The yarn flaws originate in the manufacturing process, their appearance being determined by the quality of the raw material and the technological process (equipment, technological parameters, technical condition of equipment and accessories, organization of the manufacturing process). The rare yarn flaws are local manifestations of the structural irregularities characterized by exceeding the rated values of the yarn diameter/length density within the limits of (−30/−100%); (+100/+400) manifested on sections whose length can be situated between 0.1/32cm (Neculaiasa et al., 2004).

Even if the spinning mills produce a relatively uniform yarn, the irregularity of the yarn diameter cannot be entirely avoided. That is why it is necessary to make a difference between the accepted yarn irregularity and its flaws.

2. Materials and Methods

2.1. Materials

In order to appreciate the efficiency of the cleaning operation, short

segment irregularities (U%), irregularities frequency within 1000 m of yarn and the rare flaw frequency/100 km of yarn before and after the cleaning operation have been analyzed for the following yarn assortment:

− yarn Nm 50/l (67% PES + 33% cotton); − yarn Nm 70/l (67% cotton + 33% PES); − yarn Nm 85/2 (67% PES + 33% cotton); − yarn Nm 100/2 (67% PES + 33% cotton). Each yarn was cleaned in three variants of clearer adjustment: R1 – representing L= 3; D= 2, N= 7; R2 – representing L= 2; D= 2; N= 7; R3 – representing L= 2, D=2; N= 5.

where: the selector L performs the adjustment for establishing the removed flaws length; selector D − adjustment for establishing the removed flaws thickness, and selector N − adjustment for establishing the thickness of short flaws.

The flaws eliminated by means of the electronic clearer were classified in 16 classes of flaws, that are grouped as follows:

A − flaws with the length between 0.01 and 1 cm; B − flaws with the length between 1.00 and 2.00 cm; C − flaws with the length between 2.00 and 4.00 cm; D − flaws with the length over 4 cm.

Thickness classes are symbolised by:

Bul. Inst. Polit. Iaşi, t. LIX (LXIII), f. 1-2, 2013 11

1 − thicknesses of 100%-150% from rated average yarn thickness; 2 − thicknesses of 150%-250%; 3 − thickness of 250-400%; 4 − thicknesses over 400%.

2.2. Methods

The flaws distribution follows the law of rare events, therefore the flaw detection, measurement and frequency determination implies the analysis of a long yarn length (100 km), to provide statistical results which motivates the “on-line” control applied within the spooling technological process.

The detection, frequency determination, classification and cleaning of rare flaws from cotton-type yarns were carried out by means of the Leophe FR-30 electronic cleaners installed on the Mettler spoolers.

The cleaning is the operation which permits detection and removal of yarn flaws, performed during the spooling process. The removal of a flaw implies stopping the spooler, which affects the machine yield.

As a compromise between quality and production, the choice of an optimum adjustment on the yarn clearer means in fact the avoidance of a large number of flaws with minimum production diminution, which can only be done by accurately establishing the cleaning limits.

The principle of cleaners’ adjustment is based on flaws classification into the following categories:

− long flaws (length ranging between 1÷24 cm, while their thickness is tolerable, i.e. 1.2÷1.8 times the rated diameter);

− short flaws (whose tolerable length ranges between 0.5÷10 cm, but their thickness 1.8÷3.0 times the rated diameter, cannot be neglected);

− twist yarn (flaw with a very big length, arisen from two rovings spun together or, occasionally, two joined yarns).

3. Results and Discussions

In order to control the reproducibility of determinations and to eliminate the influence of non-uniform distribution of rare flaws along the yarns, the analyses were performed on the same yarn section.

In parallel with these determinations, the number of breakages reported per 1 kg of processed yarn was recorded for every yarn and adjustment variant.

The results of the analyses performed on the four articles proposed for study are synthetically presented in terms of the following aspects:

• frequency of rare flaws per 100 km yarn before and after the cleaning operation, according to the Cassimat system. In order to make the result processing and interpretation easier, the following symbols were used:

V1 – version of yarn destined to cleaning, with R1;


V1* − the same cleaned yarn with R1;

V2 − version of yarn destined to cleaning, with R2; V2

* − the same cleaned yarn with R2; V3 – version of yarn destined to cleaning, with R3; V3

* − the same cleaned yarn with R3. • The qualitative aspect of the studied yarns was considered by

including them in Uster - Classimat quality levels, for each class apart, as well as for categories of flaws conventionally defined by I.N.C.D.T.P. Bucharest;

• For a more efficient comparison of the qualitative level of various yarn types, taking into consideration their content of rare flaws, these flaws were grouped as follows:

T − total number of flaws, including the flaws from all the classes; D − thick and long flaws, respectively severe and damaging flaws; DL – a wider range of thick and long flaws, respectively severe and

damaging flaws; C − short flaws; CL – a wider range of relatively short flaws of limited thickness; I − intermediate flaws. • The efficiency of the cleaning stage has been exemplified for the yarn Nm

50/l by a graphical representation (Fig. 1), which illustrates the relative decrease in frequency of the rare flaws (reported to the same yarn length of 100 km).

The relative frequencies of the flaws grouped as presented above have been summarized in Table 1.

From the performed analysis, one can notice that for the single yarns, the frequencies of the flaws from the classes A, B and C, before and after cleaning, are situated on the steps of world level 25% ÷ 75% from the Uster statistics, while the flaws from D category exceed the 95% world level step.

After cleaning, the flaws corresponding to the thickness classes 3 and 4 are considerably eliminated in the case of all the performed adjustments. The number of flaws from the length classes D1, D2, D3 and D4 is smaller in the case of a tighter adjustment, while those corresponding to the class Dl (flaw length exceeds 4 cm, flaw thickness up to 150% of the rated value) remain at a high level (around 95%) even after cleaning.

The percentage diminution of the flaws from category T is severe in the case of single yarns, while at the twist yarns no significant differences between the values corresponding to the three utilized adjustment versions are recorded.

The flaws from categories D and DL are considerably diminished for all the adjustment versions, more spectacular diminutions being recorded for single yarns in the case of using the R3 adjustment for the yarn Nm 50/l, so that the number of flaws recorded and classified close to the world level step of 75% is reduced, being under the 25% world level step.

In the case when the R1 and R2 adjustment variants are used, the differences are insignificant for the twist yarn.


V1

V1 V1

V1

V1 V1

V2

V2 V2

V2 V2

V2

V3

V3

V3

V3 V3

V3

0

10

20

30

40

50

60

70

80

90

100

T D DL C CL I

Categories of flawes

Relative freqency (%)

V1 V2 V3

Fig. 1 − Graphic of the variation of flaws after cleaning, for the yarn Nm 50/l.

Table 1 The Relative Frequencies of the Flaw Number Grouped within Categories

Cleaning stage efficiency, [%] Categories

of flaws

Yarn fineness 100

1V

*1V1V −

100

2V

*2V2V −

100

3V

*3V3V −

T 22.37 13.02 13.5 D 54.16 71.73 86

DL 53.44 72.58 73.33 C 24.11 6.7 8.6

CL 19.78 6.2 7.1 I

Nm 50/1

18.75 22.85 28.2 T 38.17 20.88 13.78 D 66.45 67.94 69.87

DL 64.51 66.49 70.09 C 36.88 14.83 10.5

CL 36.73 17.51 11.9 I

Nm 70/1

53.28 45.62 4.5 T 10.16 12.88 9.81 D 63.15 79.31 81.38

DL 69.23 72.72 74.35 C 3.01 0.74 1.42

CL 3.8 4.9 0.6 I

Nm 85/2

17.64 21.05 2.72 T 5.71 7.04 9.9 D 39.39 72.41 72.97

DL 35.89 65.78 71.42 C 2.98 0.31 1.2

CL 2.49 0.55 2.01 I

Nm 100/2

9.09 12.5 39.39


The influence of adjusting the electronic cleaners for each class of flaws (Classmat classification) and their classification according to the world quality levels is presented in Fig. 2; one can notice that, irrespective of adjustment, they are considerably reduced after cleaning, especially what concerns the flaws corresponding to the thickness classes 3 and 4, those of length classes C and D, being situated close to the world level steps of 5% and 23%.

4. Conclusions

1. Irrespective of the utilized adjustment version, the number of rare

flaws/100 km decreases for both each flaw class (Classimat classification) and each flaw category (according to the I.C.T. – Bucharest classification).

2. Irrespective of the utilized adjustment version, the cleaning significantly diminishes the flaws corresponding to the length classes C and D, therefore of the flaws with the length exceeding 2 cm, and of the thick flaws from classes A4 and B4.

3. Irrespective of the quality level to which they belonged prior to cleaning, the flaw corresponding to the length class A (0.1-1 cm) do not suffer essential modifications for none of the three adjustments.

Fig. 2 − Variation of the rare flaws/100 km of yarn, as compared to the Uster Classimat world levels.


4. Important decrease of the flaw number is recorded starting with the length class B and thickness classes 3 and 4, and continuing especially at the other length classes (C and D).

5. By investigating the cleaning induced modification of the flaw number in terms of categories (the I.C.T. classification), an important diminution of the flaws from categories D and DL can be noticed for all the single yarns. Bigger values of the percentage diminution of the flaw number are obtained for R2 (L-2; D-2; N-7) and R3 (L-2, D-2; N-5) adjustments, yet the total flaw number (T category) decreases when using the R1 (L-3; D-2; N-7) adjustment, as one can notice in Table 1.

6. In the case of twist yarns cleaning (Nm 85/2 and Nm 100/2), for all the adjustments, percentage decreases of the number of flaws from category T remain approximately the same, the differences in term of the utilized adjustment version being obtained at flaw from category D. The number of these flaws decreases when a tighter adjustment is used.

7. In favour of the first adjustment pleads only the number of breakages/kg, which is much smaller than that obtained for variant R2; yet, it is worth mentioning that this parameter does not exceed the rated value for the both adjustments.

8. The tendency of yarn manufacturers to use too tight adjustments, as the result of too high quality requirements, does not solve the problem of yarns quality. The tight adjustment does not modify the total flaw number.

REFERENCES Neculăiasa M., Hristian L., Metrologie Textilă. Performantica Publishing House, Iaşi

(2004). VlăduŃ N., Copilu V., Roll M., Florescu N., Filatura de bumbac. Tehnologii moderne de

laminare şi filare. Ed. Tehnică Bucureşti (1978).

ASPECTE PRIVIND CURĂłAREA FIRELOR SIMPLE ŞI RĂSUCITE TIP BUMBAC

(Rezumat)

În lucrare sunt prezentate rezultatele experimentale privind eliminarea

defectelor rare din fire tip bumbac cu ajutorul curăŃitoarelor electronice Leophe FR-30 montate pe maşinile de bobinat Mettler. FrecvenŃa şi forma defectelor permite identificarea unor relaŃii cauză-efect la nivelul fazelor procesului tehnologic de obŃinere a firelor, ceea ce permite acŃiuni corective, parŃiale, eliminarea defectelor dăunătoare a


căror apariŃie nu poate fi evitată, se realizează prin curăŃirea firelor în faza tehnologică de bobinare.

PrezenŃa defectelor (agravată prin creşterea frecvenŃei şi a dimensiunilor) diminuează prelucrabilitatea firelor şi în final aspectul Ńesăturilor şi tricoturilor produse din acestea. Gravitatea defectelor firelor se stabileşte pe baza criteriului tipodimensional de clasificare, care permite stabilirea unor limite de control obiective. Pentru aprecierea nivelului calitativ al firelor şi eficienŃa operaŃiei de epurare au fost analizate neregularităŃile pe porŃiuni scurte (U %), frecvenŃa imperfecŃiunilor pe 1000 m fir şi frecvenŃa defectelor rare/100 km fir înainte şi după operaŃia de epurare pentru următoarea gamă de fire: fir Nm 50/1 (67% pes + 33% bumbac); fir Nm 70/1 (67% bumbac + 33% pes); fir Nm 85/2 (67% pes + 33% bumbac); fir Nm 100/2 (67% pes + 33% bumbac).




THE PROPERTIES OF COTTONISED FLAX/COTTON BLENDED ROTOR SPUN YARNS

BY

COSTICĂ SAVA and MARIANA ICHIM∗∗∗∗



Received: April 12, 2013 Accepted for publication: April 26, 2013

Abstract. Over the last two decades the interest in processing blends of flax

fibers and cotton on the cotton processing line has been increased continuous. In comparison to cotton spinning system, the flax spinning system is more labour-consuming and costly. One possibility to process blends of cotton and flax on the cotton processing line is to modify the technical flax fibres by cottonisation, which yields cotton-like fibres in terms of length and fineness.

This paper presents the characteristics of Nm 10, Nm 17 and Nm 34 rotor spun yarns from 30% cottonised flax and 70% cotton blend. All-cotton yarns of similar finesses were spun for comparison purposes. In comparison to all-cotton yarns, the cottonised flax/cotton blended yarns have lower tenacity, higher strength irregularity, lower breaking elongation, higher Uster irregularity and higher number of imperfections per 1000 m. In order to maintain the number of yarn breakages to an acceptable level, higher twist has been inserted to the cottonised flax/cotton blended yarns. The use of a higher twist in the case of the flax/cotton yarns decreases the productivity of the rotor spinning machine.

The yarns spun from cottonised flax/cotton blends create visual effects in the resulting fabric due to their so popular “Linen Look”.

Key words: cottonisation, flax/cotton blend, rotor yarn.


18 Costică Sava and Mariana Ichim

1. Introduction

Over the last two decades the interest in processing blends of flax fibres and cotton on the cotton processing line has been increased continuous. Both flax and cotton are natural cellulosic fibres of vegetable origin with a cellulose content of about 95% in cotton and about 71% in flax (Foulk et al., 2007). Although the constituent polymer is the same, the properties and the processing lines of the two categories of fibres are very different. Cotton fibres are single-celled extensions of the seed epidermis, while flax fibres, separated from the non-fibre tissues in the plant stem by retting, are multi-cells technical fibres (Sava & Ichim, 2005; MustaŃă, 2007). The longitudinal view of a cotton fibre is a twisted ribbon-like and the appearance of the fibre cross-section is referred as being kidney-shaped. Flax fibres are made of bundles of elementary fibres having a spindle-like shape and a polygonal (mostly pentagonal) cross-section. The elementary fibres are joined together with middle lamellae containing hemicelluloses, pectic substances, and lignin (MustaŃă, 2004; Cierpucha et al., 2004, Cierpucha et al., 2006).

The length of cotton fibres varies from a few millimetres to 55 mm, while the length of the flax technical fibres ranges between 40 cm and 125 cm. Furthermore, the difference in the fibre finesses is noticeable. Metrical number lies from Nm 3000 to Nm 9000 for cotton, and from Nm 400 to Nm 800 for technical flax fibres (Sava & Ichim, 2005; Gribincea, 2008). As a result, the cotton and the technical flax fibres are processed on different spinning systems. In comparison to cotton spinning system, the flax spinning system is more labour-consuming and costly. One possibility to process blends of cotton and flax on the cotton processing line is to modify the technical flax fibres by cottonisation, which yields cotton-like fibres in terms of length and fineness.

Cottonisation is the process of removing the lignified pectins from the middle lamella, thereby allowing the dis-aggregation of the elementary fibres contained in the long technical fibre. The elementary fibres are similar in length and fineness to cotton fibres and thus their blend can be processed on cotton spinning system with lower costs and higher productivity (http://www.jos-vanneste.com).

This paper presents the results of rotor spinning of Nm 10, Nm 17 and Nm 34 yarns from 30% cottonised flax and 70% cotton blend. All-cotton yarns of similar finesses were spun for comparison purposes.


The characteristics of the cottonised flax and cotton fibres are presented in Table 1. In respect of fineness, the cottonised flax fibres are about two times coarser than the cotton fibres. While the lengths of cottonised flax and cotton fibres are close, the short fibre content of cottonised flax is more than two times


higher than cotton short fibre content. The breaking length of cottonised flax fibres is lower by about 15% than the breaking length of cotton fibres.

Table 1 Characteristics of the Raw Materials

Characteristics Unit Cotton Cottonised flax Fineness [Nm] 5400 2615 Fibre strength [cN/fibre] 3.52 6.12 Fibre breaking length [km] 19 16 Fibre length [mm] 28 27 Short fibre content [%] 17 37 Fibre impurities [%] 1.2 1.96

The blend of cottonised flax and cotton has been processed on a modified cotton processing line, as follows:

1. Cottonised flax emulsifying and 24 h of repose at room temperature. 2. Manual blending employing ‘sandwich’ (horizontal) layers. 3. Opening, cleaning and blending on an Ingolstadt blowroom and lap

formation. 4. Carding on an Unirea 4C flat card. 5. Sliver lap formation; 24 card slivers are creeled, drafted and

compressed on a Textima sliver lap machine and the sliver lap is wound into a cylindrical roll.

6. Second carding for a better division of multi-cells flax fibres; three sliver laps are fed simultaneously at the card in order to continue the fibre individualization and the cleaning process.

7. Doubling and drafting of card slivers on an Ingolstadt draw frame. 8. Evening-up of drafted slivers on an Unirea LB draw frame. 9. Spinning on BD-200 RN rotor spinning machine.

Linear density of yarns was determined according to SR EN ISO 2060:1997 test method. The tensile properties have been measured according to SR EN ISO 2062:2010 standard on a TINIUS OLSEN H5 K-T tensile yarn tester. The length of the test specimen was 500 mm. The yarn twist was tested according to SR EN ISO 2061:2011 test method, using a clamping distance of 250 mm. Uster Tester-II was used to determine short-term irregularity of yarns, total imperfections (thin places, thick places and neps) at a speed of 25 m/min.


Yarns of Nm 10, Nm 17 and Nm 34 fineness were obtained from both

30 % cottonised flax/70 % cotton and all-cotton blends. The twist of yarns was adjusted at a level for which the number of yarn breakages was acceptable.

Fig. 1 presents the tenacity of yarns and Fig. 2 presents the irregularity of strength of all tested yarns. The tenacity of cottonised flax/cotton blended


yarns is lower than the tenacity of cotton yarns, but the requirements of quality standard are met.

4

5

6

7

8

9

10

11

10 17 34Yarn fineness, Nm

Yar

n te

naci

ty, c

N/t

ex

cotton flax/cotton

Fig. 1 − Tenacity of yarns.

0

5

10

15

20


CV

of

brea

king

st

reng

th, %

cotton flax/cotton

Fig. 2 − Breaking strength irregularity of yarns.

The differences in yarn tenacity of all-cotton and cottonised flax/cotton

blended yarns lie between 2% and 28%. This behaviour can be explained by the fact that the cottonised flax fibres are coarser than the cotton fibres and thus the number of fibres in the cross-section of blended yarns is lower than in the case of all-cotton yarns.

With the exception of Nm 17 cottonised flax/cotton blended yarn, the CV of breaking strength of the other two blended yarn assortments are higher than the breaking strength irregularity of correspondent cotton yarns.

When compared to cotton yarns, the breaking elongation of cottonised flax/cotton blended yarns is lower with 11% to 22 % (Fig. 3), especially for the finer yarn assortments (Nm 17, Nm 34).


4

5

6

7

8

9


Bre

akin

g el

onga

tion

, %

cotton flax/cotton

Fig. 3 − Breaking elongation of yarns.

In order to maintain the number of yarn breakages to an acceptable level, higher twist has been inserted to the cottonised flax/cotton blended yarns (Fig. 4). The differences between the twist of all-cotton and cottonised flax/cotton blended yarns ranged between 20% and 30%. The use of a higher twist in the case of the flax/cotton yarns decreases the productivity of the rotor spinning machine.

200300400500600700800900


Tw

ist,

tpm

cotton flax/cotton

Fig. 4 − Twist values of yarns.

Mass irregularity of the yarns measured by CV Uster and the number of

imperfections per 1000 m (with the exception of thin places) show better values for the cotton yarns (Figs. 5,…,8). Because the cotton fibres are two times finer than the cottonised flax fibres, the number of fibres in the cross-section of a cotton yarn is higher than in the cross-section of flax/cotton yarn. Also, the short fibre content is two times higher in the case of cottonised flax.


Fig. 5 − Uster irregularity of yarns. Fig. 6 − Thin places/1000 m of yarns.

Fig. 7 − Thick places/1000 m of yarns. Fig. 8 − Neps/1000 m of yarns.

4. Conclusions

The technology developed for processing of 30% cottonised flax/70% cotton blends on the cotton spinning system allows the production of rotor spun yarns ranging from Nm 10 to Nm 34.

1. In comparison to all-cotton yarns, the cottonised flax/cotton blended yarns have lower tenacity (but above the value specified in the quality standard for all-cotton yarns), higher strength irregularity, lower breaking elongation, higher Uster irregularity and higher number of imperfections per 1000 m. This behaviour can be explained by the differences between the two categories of fibres in respect of fibre fineness, short fibre content and fibre structure.

2. In order to maintain the number of yarn breakages to an acceptable level, higher twist has been used for the cottonised flax/cotton blended yarns. Therefore, the productivity of the rotor spinning machine has been reduced.

3. In cottonised flax/cotton blends rotor spinning, the breakage rate is the lowest in the case of Nm 17 yarn assortment.

4. The yarns spun from cottonised flax/cotton blends create visual effects in the resulting fabric due to their so popular “Linen Look”.


REFERENCES Cierpucha W., Czaplicki Z., Mańkowski J., Kołodziej J., Zaręba S., Szporek J.,

Blended Rotor-Spun Yarns with a High Proportion of Flax. Fibres & Textiles in Eastern Europe, 14, 5 (59), 80 (2006).

Cierpucha W., Kozłowski R., Mańkowski J., Waśko J., Mańkowski T., Applicability of

Flax and Hemp as Raw Materials for Production of Cotton-like Fibres and

Blended Yarns in Poland. Fibres & Textiles in Eastern Europe, 12, 3 (47), 13 (2004).

Foulk J.A., Dodd R.B., McAlister D., Chun D., Akin D.E., Morrison H., Flax-Cotton

Fibre Blends: Miniature Spinning, Gin Processing, and Dust Potential. Industrial Crops and Products, 25, 8 (2007).

Gribincea V., Fibre textile. Ed. Performantica, Iaşi (2008). MustaŃă A., Procese şi maşini în filatura inului, cânepei, iutei. Part. I, Ed.

Performantica, Iaşi (2007). MustaŃă A., Mechanical Behaviour in the Wet and Dry Stage of Romanian Yarns Made

from Flax and Hemp. Fibres & Textiles in Eastern Europe, 12, 3 (47), 7 (2004). Sava C., Ichim M., Filatura de bumbac. Tehnologii şi utilaje în preparaŃie. Ed.

Performantica, Iaşi (2005). http://www.jos-vanneste.com/start/products/short_staples/en, Short Staple Ring and

Rotor Spinning (accessed at 9.04.2013).

PROPRIETĂłILE FIRELOR FILATE CU ROTOR DIN AMESTEC DE IN COTONIZAT ŞI BUMBAC

(Rezumat)

În ultimele două decenii, interesul pentru prelucrarea amestecurilor de in şi

bumbac pe sistemul de filare tip bumbac a crescut continuu. În comparaŃie cu sistemul de filare tip bumbac, sistemul de filare a fibrelor de in este mai costisitor şi necesită mai multă forŃă de muncă. Una dintre posibilităŃile de prelucrare a amestecurilor de bumbac şi in pe sistemul de filare tip bumbac constă în modificarea fibrelor tehnice de in prin cotonizare, obŃinându-se astfel fibre tip bumbac din punct de vedere al lungimii şi fineŃii.

Această lucrare prezintă caracteristicile firelor cu fineŃea Nm 10, Nm 17 şi Nm 34 filate cu rotor din amestec de 30% in cotonizat şi 70% bumbac. Pentru comparaŃie, au fost filate fire din bumbac 100% cu fineŃe similară.

În comparaŃie cu firele din bumbac 100%, firele din amestec de in cotonizat şi bumbac au tenacitate mai mică, neuniformitate la rezistenŃă mai mare, alungire la rupere mai mică, neuniformitate Uster mai mare şi număr mai mare de imperfecŃiuni pe 1000 m de fir. Pentru a menŃine numărul de ruperi de fir la un nivel acceptabil, firelor din amestec de in cotonizat şi bumbac li s-a conferit o torsiune mai mare. Utilizarea unei torsiuni mai mari a condus la reducerea productivităŃii maşinii de filat cu rotor.

Firele filate din amestecuri de in cotonizat şi bumbac crează efecte vizuale în Ńesături datorită popularului “aspect de in”.




REDUCED MARKOV CHAIN FOR A

WEAVING MACHINES INTERFERENCE PROBLEM

BY

DOINA CAŞCAVAL∗∗∗∗


Faculty of Textiles & Leather Engineering and Industrial Management Received: April 11, 2013 Accepted for publication: April 27, 2013

Abstract. A weaving machines interference problem is treated in this

paper. For a group of weaving machines allocated to the weaver, two indicators must be evaluated: the efficiency of the weaving machines and the work loading for the weaver. Two different approaches are available: analytical approach, based on Markov chains, and simulation. A reduced Markov model able to evaluate with accuracy the two indicators previously defined is proposed in this paper. A case study for five weaving machines, in which exact and approximate results are presented, demonstrates the effectiveness of this simplified analytical approach.

Key words: weaving process, interference time, Markov model.

1. Introduction

The weaving process is a discrete event one because the warp yarns and

the filling yarn break off at random instants. In case a weaving machine (loom) is down because a yarn has broken, a weaver (loom operator) must remedy the broken yarn and then start up the loom again. In other words, a weaving machine is a system with repair. The problem of allocation of looms to the loom ∗Corresponding author; e-mail: [email protected]

26 Doina Caşcaval

operators is a very important one in a large weaving mill. The prediction of the loom efficiency and the weaver work loading according to the number of looms allocated to the weaver is a machines interference problem. The problem of allocation of looms in weaving is widely dealt with in textile literature, both from a theoretical and a practical point of view (see for example, Bona, 1993; Caşcaval, 1999a; Caşcaval & Ciocoiu, 2000b).

The analytical approach for the machines interference problem is based on the theory of queues (see for example, Delaney &Vaccari, 1999; Trivedi, 2002). The standard model is a Markov chain for which the steady−state probabilities are required. For a Markov chain with s states, a system with s

linear equations must be solved. This method is simple in essence but, unfortunately, the state space of the Markov chain increases rapidly (Bona, 1993; Caşcaval, 1999b). For any sizable practical problem s becomes very large and the solution time becomes very long, so that, the classical approach is difficult to apply. When the number of states of Markov chain is very large, the two approaches available to deal with this problem are to either tolerate the largeness or avoid it. In this work, a largeness avoidance technique for an approximate evaluating of the loom efficiency is discussed.

The simulation is a complementary approach for machine interference problem (Caşcaval, 1999a; Caşcaval & Ciocoiu, 2000a). A simulation program based on a stochastic coloured Petri net has been used to validate the all analytical results presented in this paper.

The remainder of this paper is organized as follows. In Section 2 the interference problem concerning the weaving process is defined. To illustrate the analytical method based on Markov chains, able to solve this interference problem, a simple case with three weaving machines served by one weaver is also presented in this section. A simplified analytical approach based on state-space largeness avoidance is proposed in Section 3. This method avoids the constructing of whole space of states and allows a good accuracy in evaluating the efficiency of the weaving machines and the work loading for the weaver. Finally, some conclusions regarding this work are drawing in Section 4.

2. Problem Formulation and Classical Analytical Approach

Consider a weaving process completely known from a statistical point of view. The stochastically model of the weaving process includes four primary random variables, namely:

• Time to break off a warp yarn − let Wλ be the breakage rate of the

warp yarns;

• Time to break off the filling yarn − let Fλ the breakage rate of the filling yarn;


• Time to remedy a warp breakage − let Wµ be the remedying rate of warp breakages;

• Time to remedy a filling breakage − let Fµ the remedying rate of filling breakages.

In the case where all the parameters Wλ , Fλ , Wµ and Fµ are known,

we have to estimate the efficiency of the looms (EF) and the work loading for the weaver (WL) according to the number m of looms allocated to the loom operator.

This prediction problem is treated under the following assumptions: − all primary random variables are exponentially distributed;

− the weaving process is in a steady−state condition;

− any loom is either up or down, with no intermediate states;

− all break events are stochastically independent.

Let us consider three identical weaving machines allocated to the weaver (m = 3). For any loom, three distinct states must be taken into account: the machine is up (↑), the machine is down because a warp yarn has broken (↓-w), and the machine is down because the filling yarn has broken (↓-F). Because all the looms are identical, a Markov chain with thirteen states as presented in Table 1 is appropriate to describe this weaving process. Symbol * denotes the weaving machine under remedying. The graph of states is presented in Fig. 1. Based on this graph with n states (n = 13), the square matrix nnjiaM ×= ][ , of

transition rates between states is then carried out. The location ( ji, ) in matrix

M, ji ≠ , represents the transition rate from state j to state i, whereas the value

of a location ),( ii , ..., ,2,1 ni ∈ , is equal to the sum of the transition rates in column i , taken with minus.

Let ip be the steady-state probability of ,iS ,,...,2,1 ni∈ and the

vectors Tnn pppP ]..., ,,[ 211 =× and T

nZ ]0..., ,0,0[1 =× . To determine the

steady-state probabilities nppp ..., ,, 21 , the set of linear eq. (1) must be solved.

1 2 1n

M P Z

p p p

⋅ = + + ⋅⋅ ⋅ + =

(1)

After that, the loom efficiency can be obtained by using eq. (2).

2 3 4 5 6 71

2( )100 %

3 3

p p p p p pEF p

+ + + + = + + ⋅

(2)

28 Doina Caşcaval

Table1 The States of Markov Chain for three Looms Allocated to a Weaver

Si State of Markov chain Comments

S1 3(↑) All the three weaving machines are up

S2 2(↑), 1(↓-w)*

S3 2(↑), 1(↓-F)* Two weaving machines are up and the other one is down

S4 1(↑), 1(↓-w), 1(↓-w)*

S5 1(↑), 1(↓-w)*, 1(↓-F)

S6 1(↑), 1(↓-w), 1(↓-F)*

S7 1(↑), 1(↓-F), 1(↓-F)*

One weaving machine is up and the two other are down

S8 2(↓-w), 1(↓-w)*

S9 1(↓-w), 1(↓-w)*, 1(↓-F)

S10 1(↓-w)*, 2(↓-F)

S11 2(↓-w), 1(↓-F)*

S12 1(↓-w), 1(↓-F), 1(↓-F)*

S13 2(↓-F), 1(↓-F)*

All the three weaving machines are down

S1

S2 S3

S4 S5 S6 S7

S8 S9 S10 S11 S12 S13

3λW

µW µF

3λF

2λWµW

µF2λF 2λW

µW µF2λF

µW µF

λW λF λW

µW

λF λW

µF

λF λW

µFµW

λF

Fig. 1 − The Markov chain for three weaving machines served by one weaver.

The work loading for the loom operator is given by eq. (3).

( ) % 1001 1 ⋅−= pWL (3)

With thirteen states, the Markov chain is quite complicated even for this

simple case. For the case where four looms are allocated to the weaver, the


Markov chain includes twenty one states (Caşcaval & Ciocoiu, 2000b). Usually, a weaver serves up to ten looms when the graph grows up to one hundred eleven states. For this reason, a simplified approach is necessary to overcome the complexity of Markov models. A classical approach for reducing the Markov chain is based on a simplified stochastically model with only two primary random variables (Bona, 1993). Another method reduces the Markov model by applying of so called series or parallel transformation rules (Caşcaval & Caşcaval, 2005a; Caşcaval & Caşcaval, 2005b). In this paper a new approximate method based on a reduced Markov chain is discussed. The point is to reduce the state space of Markov chain by neglecting the states with a very low steady-state probability, like the states of the lower level where all the looms are down. As follows, this method is illustrated for the case in which five looms are allocated to the weaver.

3. A Simplified Analytical Approach

Consider five weaving machines allocated to the weaver. The Markov chain that allows an exact evaluation of the loom efficiency is composed of

31=n states as presented in Table 2. The transition rates between states are also presented in this table. The steady-state probabilities can be obtained by solving the set of linear eq. (1). Based on these steady-state probabilities, the loom efficiency is given by eq. (4). For the weaver work loading, the same eq. (3) can be used.

( ) ( ) ( )13121110987654321 5

2

5

3

5

4pppppppppppppEF ++++++++++++=

( )22211918171615145

1pppppppp ++++++++ . (4)

Observe that, in the states ÷22S 31S all the five looms are down. A

reduced Markov chain can be obtained by neglecting these ten states with much lower steady-state probability values. For the reduced model, with only 21=n states, the steady-state probabilities can also be obtained by solving the set of linear eq. (1), and then, the loom efficiency can be calculated by using eq. (4). The weaver work loading is given by the same eq. (3). To evaluate the estimation accuracy by using this approximate approach, some numerical results are presented as follows. Take the following parameters of primary random variables: =Wλ 2.613 and =Fλ 1.812 breaks/h; =Wµ 51.87 and =Fµ 40.65

remedies/h, and consider the cases with two, three, four, and five looms allocated to the user. For the extended Markov chains, the steady-state probabilities are presented in Table 3.

30 Doina Caşcaval

Table 2

The States and the Transition Rates Between States for Five Weaving Machines

iS State description Transition rates from current state

1S 5(↑) a1, 2 = µW, a1, 3 = µF

2S 4(↑), 1(↓-w)* a2, 1 = 5λW, a2, 4 = µW, a2, 6 = µF

3S 4(↑), 1(↓-F)* a3, 1 = 5λF, a3, 5 = µW, a3, 7 = µF

4S 3(↑), 1(↓-w), 1(↓-w)* a4, 2 = 4λW, a4, 8 = µW, a4, 11 = µF

5S 3(↑), 1(↓-w)*, 1(↓-F) a5, 2 = 4λF, a5, 9 = µW, a5, 12 = µF

6S 3(↑), 1(↓-w), 1(↓-F)* a6, 3 = 4λW

7S 3(↑), 1(↓-F), 1(↓-F)* a7, 3 = 4λF, a7, 10 = µW, a7, 13 = µF

8S 2(↑), 2(↓-w), 1(↓-w)* a8, 4 = 3λW, a8, 14 = µW, a8, 18 = µF

9S 2(↑), 1(↓-w), 1(↓-w)*, 1(↓-F) a9, 4 = 3λF, a9, 5 = 3λW, a9, 15 = µW, a9, 19 = µF

10S 2(↑), 1(↓-w)*, 2(↓-F) a10, 5 = 3λF, a10, 16 = µW, a10, 20 = µF

11S 2(↑), 2(↓-w), 1(↓-F)* a11, 6 = 3λW

12S 2(↑), 1(↓-w), 1(↓-F), 1(↓-F)* a12, 6 = 3λF, a12, 7 = 3λW

13S 2(↑), 2(↓-F), 1(↓-F)* a13, 7 = 3λF, a13, 17 = µW, a13, 21 = µF

14S 1(↑), 3(↓-w), 1(↓-w)* a14, 8 = 2λW, a14, 22 = µW, a14, 27 = µF

15S 1(↑), 2(↓-w), 1(↓-w)*, 1(↓-F) a15, 8= 2λF, a15, 9= 2λW, a15, 23 = µW, a15, 28= µF

16S 1(↑), 1(↓-w), 1(↓-w)*, 2(↓-F) a16, 9 = 2λF, a16, 10= 2λW, a16, 24 =µW, a16, 29=µF

17S 1(↑), 1(↓-w)*, 3(↓-F) a17, 10 = 2λF, a17, 25 = µW, a17, 30 = µF

18S 1(↑), 3(↓-w), 1(↓-F)* a18, 11 = 2λW

19S 1(↑), 2(↓-w), 1(↓-F), 1(↓-F)* a19, 11 = 2λF, a19, 12 = 2λW

20S 1(↑), 1(↓-w), 2(↓-F), 1(↓-F)* a20, 12 = 2λF, a20, 13 = 2λW

21S 1(↑), 3(↓-F), 1(↓-F)* a21, 13 = 2λF, a21, 26 = µW, a21, 31 = µF

22S 4(↓-w), 1(↓-w)* a22, 14 = λW

23S 3(↓-w), 1(↓-w)*, 1(↓-F) a23, 14 = λF, a23, 15 = λW

24S 2(↓-w), 1(↓-w)*, 2(↓-F) a24, 15 = λF, a24, 16 = λW

25S 1(↓-w), 1(↓-w)*, 3(↓-F) a25, 16 = λF, a25, 17 = λW

26S 1(↓-w)*, 4(↓-F) a26, 17 = λF

27S 4(↓-w), 1(↓-F)* a26, 18 = λW

28S 3(↓-w), 1(↓-F), 1(↓-F)* a28, 18 = λF, a28, 19 = λW

29S 2(↓-w), 2(↓-F), 1(↓-F)* a29, 19 = λF, a29, 20 = λW

30S 1(↓-w), 3(↓-F), 1(↓-F)* a30, 20 = λF, a30, 21 = λW

31S 4(↓-F), 1(↓-F)* a31, 21 = λF


Table 3

Steady-State Probability Values for the Cases: m = 2, m = 3, m = 4 and m = 5

2 looms 3 looms 4 looms 5 looms

Si pi Si pi Si pi Si pi

Level 1 S1 0.82789 S1 0.74405 S1 0.66168 S1 0.58204

S2 0.08414 S2 0.11358 S2 0.13405 S2 0.14538 Level 2

S3 0.07287 S3 0.09804 S3 0.11704 S3 0.13126

S4 0.00424 S4 0.01161 S4 0.01898 S4 0.02846

S5 0.00294 S5 0.00886 S5 0.01709 S5 0.02452

S6 0.00468 S6 0.00858 S6 0.02048 S6 0.02544 Level 3

S7 0.00325 S7 0.01137 S7 0.01548 S7 0.02740

S8 0.00058 S8 0.00196 S8 0.00426

S9 0.00085 S9 0.00326 S9 0.00709

S10 0.00031 S10 0.00145 S10 0.00710

S11 0.00073 S11 0.00237 S11 0.00279

S12 0.00106 S12 0.00344 S12 0.00434

Level 4

S13 0.00038 S13 0.00136 S13 0.00389

S14 0.00010 S14 0.00043

S15 0.00023 S15 0.00104

S16 0.00019 S16 0.00127

S17 0.00005 S17 0.00057

S18 0.00015 S18 0.00032

S19 0.00033 S19 0.00073

S20 0.00024 S20 0.00080

Level 5

S21 0.00006 S21 0.00035

S22 0.00002

S23 0.00007

S24 0.00010

S25 0.00007

S26 0.00002

S27 0.00002

S28 0.00006

S29 0.00008

S30 0.00006

Level 6

S31 0.00002

32 Doina Caşcaval

Observe that, for the states where all the looms are down, the exact steady-state probability values are much lower on compared with all other states (values highlighted in Table 3). For this reason, these states can be neglected in an approximate approach.

Table 4 presents numerical results with respect to the loom efficiency (EF) and the weaver work loading (WL) for all these four case studies. To illustrate the accuracy of this simplified method, both exact and approximate values are presented in this table.

Table 4

Machine Efficiency (EF) and Weaver Work Loading (WL) for Some Case Studies

EF, [%] WL, [%]

Exact value

Approximate value

Estimation error, [%]

Exact values

Approximate values

2 looms 90.64 92.62 2.18 28.89 25.72

3 looms 89.86 90.39 0.59 42.00 41.00

4 looms 88.95 89.04 0.10 54.63 54.19

5 looms 87.97 88.01 0.05 65.72 65.50

It can be observed that the estimation error is greater for a small number

of looms but it decreases rapidly once the number of looms allocated to the weaver increases. For a number of looms greater or equal to four, this approximate method ensures a very good accuracy. Of course, the accuracy also depends on the values of parameters of the primary random variables ( ,Wλ ,Fλ ,Wµ )Fµ .

4. Final Remarks

The simplified analytical method based on reduced Markov chains

ensures good estimation when the number of looms is greater or equal to three-four. Usually, the number of looms allocated to the weaver grows up to ten or even more. In those cases, the Markov model can be reduced even more by neglecting and other states from lower levels. This approximate method is important from both theoretical and practical points of view.

REFERENCES

Bona M., Statistical Methods for the Textile Industry. Texilia, Torino, Italy (1993). Caşcaval D., ContribuŃii la perfecŃionarea conducerii în timp real a proceselor din

industria textilă. Teză de doctorat, Universitatea Tehnică „Gheorghe Asachi” din Iaşi (1999a).


Caşcaval D., Caşcaval P., Analytical and Simulation Approach for Efficiency

Evaluation of the Weaving Machines with Filling Break Tolerance. WSEAS Trans. on Information Science & Applications, 2, 12, 2243−2251 (2005a).

Caşcaval D., Caşcaval P., Markov Chains Based Modelling of Weaving Machines with

Filling Break Tolerance and Automatic Filling Repair. Bul. Inst. Polit. Iaşi, Automatică şi Calculatoare, LI (LV), 1-4, 147−156 (2005b).

Caşcaval D., Ciocoiu M., A Simulation Approach Based on the Petri Net Model to

Evaluate the Global Performance of a Weaving Process. Fibres & Textiles in Eastern Europe, 8, 3 (30), 44−47 (2000a).

Caşcaval D., Ciocoiu M., An Analytical Approach to Performance Evaluation of a

Weaving Process. Fibres & Textiles in Eastern Europe, 8, 3 (30), 47−49 (2000b).

Caşcaval D., Markov Model for Efficiency Evaluation of the Weaving Machines with

Filling Break Tolerance. Bul. Inst. Polit. Iaşi, s. Automatică şi Calculatoare, XLV (IL), 1-4, 17−25 (1999b).

Delaney W., Vaccari E., Dynamic Models and Discrete Event System. Marcel Dekker, New York (1999).

Trivedi K.S., Probability and Statistics with Reliability, Queuing and Computer Science

Applications. Wiley-Interscience, New York, USA (2002).

MODEL MARKOV REDUS PENTRU O PROBLEMĂ DE INTERFERENłĂ A MAŞINILOR DE łESUT

(Rezumat)

Lucrarea tratează o problemă de interferenŃă a maşinilor de Ńesut. Pentru un

grup de maşini deservite de un muncitor trebuie evaluat randamentul maşinilor şi gradul de încărcare a muncitorului, în funcŃie de numărul de maşini alocate. Pentru rezolvarea acestei probleme de predicŃie pot fi aplicate metode analitice bazate pe modele Markov sau tehnici de simulare numerică. În lucrare se prezintă o metodă aproximativă, bazată pe un model Markov redus, pentru evaluarea cu o bună acurateŃe a celor doi indicatori. EficienŃa acestei metode de predicŃie, în care numărul stărilor lanŃului Markov este considerabil redus, este ilustrată printr-un studiu de caz în care un muncitor deserveşte cinci maşini de Ńesut.




ASPECTS CONCERNING THE WARP STATIC TENSION ON WEAVING MACHINE

BY

IOAN CIOARĂ∗∗∗∗ and LUCICA CIOARĂ


Faculty of Textiles & Leather Engineering and Industrial Management Received: April 12, 2013 Accepted for publication: April 29, 2013

Abstract. The warp static tension represents a basic technological parameter for weaving. The value of the static tension should be adopted in accordance with the characteristics of processed yarns and the specifics of the fabric. The paper presents some technological aspects concerning the ways of obtaining warp static tension on the weaving machine. The influences of the technological parameters (advance at shed formation, the position of the back beam in relation to the position of front beam) on the value of the warp static tension are analysed.

Key words: weaving, static tension, warp yarns, technological parameters.

1. Introduction In the weaving process the warp threads are subjected to the following

strains: stretching, friction and bending. These strains are determined by the mechanisms which impose displacements in both directions, as well as guiding devices placed along the yarn path. The analysis of phenomena on the weaving machine shows applications carrying out separately or associated in various parts of the path (Cioară, 2008; Cioară, 2011; *

**, 2004). In the roll of warp -


36 Ioan Cioară and Lucica Cioară

back crossbeam area, the main tension is created by the warp feeding (let-off) mechanism and take-up mechanism. The friction is produced by the contact of the warp threads with the back crossbeam. In the warp controlling area, the yarns are subjected to friction and tensile stresses. The friction develops between blades and yarns and between neighbouring yarns during shed formation. Due to the yarn separating movement during shed formation, in the area between the warp controller and the shedding harnesses there is a cyclic strain and friction between the warp threads. In the harnesses area the yarns are subjected to tensile strain, several types of friction (yarn – yarn friction, yarn – heald friction, friction between yarns in neighbouring healds) and bending due to the repeated lifting and lowering of the shedding harnesses. The stress in the reed area is caused by tensile stress and friction.

Predominantly on the weaving machine, the warp threads will be put to tensile stresses. The total tension of the warp yarns is obtained by summing the values of the dynamic and static tensions. The dynamic tension develops only during weaving and represents about 10 to 15% of the breaking force of the yarns. The static or mounting tension of the warp yarns represents about 5 to 10% of the breaking force. Therefore the total tension of the warp can reach a level of about 15 to 25% of the breaking force of the yarns. To maintain the tensional characteristics of the warp yarns it is important to maintain the stress within the elastic range.

The static tension is the component of the warp total tension that is preset on the weaving machine (Cioară, 2008; Cioară, 2011; Marchiş & Cioară, 1986; Taloi et al., 1983). The necessary static tension is set with the help of let-off and take-up mechanisms. The static tension is required during weaving, as follows:

− For the controlled displacement of the warp yarns from the warp beam to the weaving area;

− For separating warp yarns for proper forming of shed layers; maintaining the preset tension of the warp yarns facilitates the beating of the weft yarn by the reed.

The level of static tension will be present according to the tensile properties of the yarns and the degree of compactness of the woven fabric. It is important for the weaving process to maintain the static tension as close as possible to the original value. This allows producing a uniform fabric regardless of the diameter of the warp beam.

In reality, the warp static tension is influenced by a number of factors that determine specific variations. Are highlights in this regard the factors that determine changing conditions from the conduct of warp yarns and the values for main technological parameters. The parameters for the let-off of the warp yarns are dependent on the type of system used. When using manually adjustable warp beam brake the level of static tension varies widely. These variations are created by the lack of accuracy of the worker when adjusting the


braking force of the beam. The decrease of beam radius leads to an increase of the static tension in the warp yarns; this requires the worker to manually adjust the braking force in order to decrease the yarn tension to its pre-set value. The variation interval is dependent on the experience of the staff. In the case of automated brake mechanisms, the level of static tension is maintained between predefined limits depending on the accuracy level of the brake, without the intervention of worker. This implies the continuous reduction of the braking force in relation to the radius of the warp beam. When using negative regulators the warp static tension is adjusted continuously depending on the variation of the let-off angle of the warp yarns on back roll. This angle is minimum the beam is full and increases as the beam radius decreases.

On the other side it can be mentioned that during weaving cycle the static tension is at its minimum level when the warp yarns are in the same plan (at levelling). At this moment the warp yarns have no dynamic tension and are stretched only by their static tension. The minimum level of static tension obtained at levelling (closed shed position) is also recommended when the weaving looms are stopped for longer periods of time because this position protects the tensile behaviour of the warp yarns.

This paper presents the influence of the adjustments of technological parameters on the warp static tension. The technological parameters analysed are: advance of the shed formation and the position of the back roll in relation to the front roll. This analysis provides some quantitative criteria for assessing the influences of two parameters on the variation of the static tension.

2. Materials and Methods. Experimental

A rotatable central composite design with two independent variables

was used to study the influence of two technological parameters on the warp static tension (Taloi et al., 1983): advance of the shed formation and the position of the back roll in relation to the front roll .The encoded and real values of the independent variables are presented in Table 1. The static tension at levelling was chosen as the dependent variable. The static tension was measured using an electronic tensiometer.

Table 1

Encoded and Real Values of the Independent Variables

Coded values real values

No.

Independent variables

Symbol Units of measure

−1.414 −1 0 +1 +1.414

1 Advance of the shed formation

X1 [grad] 0 10 30 50 60

2 Position of the back

rest in relation to the front rest

X2 [mm] −40 −30 0 +30 +40


The complete experimental matrix is shown in Table 2. The experiments were carried out on a conventional weaving machine at a speed of 160 rev/min. The warp yarns were 100% cotton, count Nm 10/2 and breaking strength 620 cN/yarn.

Table 2 The Experimental Matrix

Y, [cN/yarn] No.

X0 X1 X2

21X

22X X1X2 measured calculated

1 1 −1 −1 +1 1 +1 67.8 66.03 2 1 +1 −1 +1 1 −1 59.9 56.63 3 1 −1 +1 +1 1 −1 40.4 41.27 4 1 +1 +1 +1 1 +1 46 45.35 5 1 −1.414 0 2 0 0 54.6 54.72 6 1 +1.414 0 2 0 0 48.7 50.95 7 1 0 −1.414 0 2 0 61.5 64.54 8 1 0 +1.414 0 2 0 39.7 39.05 9 1 0 0 0 0 0 48.7 49.16

10 1 0 0 0 0 0 48.1 49.16 11 1 0 0 0 0 0 50 49.16 12 1 0 0 0 0 0 48.7 49.16 13 1 0 0 0 0 0 50.3 49.16

For each experimental run, the static tension was measured ten times at

levelling position. Table 2 presents the average values of the static tension. The randomness of the output values from each run was verified using

the mean square successive difference test. The aberrant values were tested using the Dixon test. Following these tests it was concluded that the experimental values presented no outliers.

The experimental data was modelled with the following equation:

Y = B0 + B1X1 + B2X2 +B1121X + B22

22X + B12X1X2 (1)

where: B1, B2, B9, B11, B22, B12 represent the equation coefficients; X1 – independent variable (advance of the shed formation); X2 – independent variable (the position of back roll in relation to the position of the front roll); Y − the output variable (the static tension at levelling).

According to the methodology presented in the literature (Taloi et al., 1983), the equation coefficients are estimated with relations:

0B = 0.2(OY) 0.1 (iiY)− ∑ (2)

iB = 0.125(iY) (3)


ijB = 0.25(ijY) (4)

(iiY) = 11Y+22Y∑ (5)

iiB = 0.125(iiY)+0.01875 (iiY) 0.1(OY)−∑ (6)

where: (OY) is the product of X0 column and Y column; (iY) − the product of

Xi column and Y column; (iiY) − the product of 2ix column and column Y;

(ijY) − the product of XiXj column and column Y. The values of the equation coefficients (1) were calculated based on the

experimental data from Table 2. The significance of these coefficients was verified using the Student test and all coefficients were found to be significant.

The adequacy of the mathematical model was tested with the Fisher test. The confidence interval was determined to be 5%.

In these conditions the equation modelling the warp static tension is:

2 21 2 1 2 1 2Y = 49.16 1.33X 9.01X +1.84X +1.32X +3.37X X− − (7)


The overall analysis of the relationship (7) shows different influences of

the technological parameters X1 and X2 on the value of the warp static tension. The linear terms determine the reverse influence of the static tension,

for positive values of the coded parameters X1 and X2. For negative values of the coded parameters X1 and X2 the influences are direct.

The terms linear coefficient values show greater influence of X1 parameter compared to X2 parameter.

The quadratic terms determine the direct influence on the value of static tension throughout the experimental area.

The mixed term has a significant direct influence on static tension in the case when the independent variables (the technological parameters) have encoded values by the same sign.

Detailed interpretation of the effects of the technological parameters is performed based on the analysis of the static tension contours shown in Fig. 1. For the minimum value of advance of the shed formation (X1 = −1.414) and back rest position changing from −1.414 to +1.414, the static tension registers a decrease of 55.6% (from the value 76.86 cN/yarn to 34.11 cN/yarn). The significant differences between the values of the static tension at the two extreme values of the position of the back rest are attributed to the asymmetric horizontal shed.


Fig. 1 – Contour plot of the static tension. The minimum static tension at levelling is obtained for to the maximum

positive back rest position (X2 = +1.414). For the average value of shed formation advance (coded value X1 = 0, real value X1 = 30º) the static tension variation is between 64 cN/thread and 40 cN/thread. The variation interval of static tension is restricted between 60.59 cN/thread and 47.59 cN/thread for the maximum value of parameter X1 (value coded +1414, real value 60º).

For the minimum back rest position (X2 = −1.414) the static tension decreases with 21.14% (from 76.84 cN/thread to 60.59 cN/thread), while the parameter X1 varies between 0º and 60º. For the back rest position X2 = 0, the variation of the static tension is placed in a smaller interval - between 48 cN/thread and 52 cN/thread. For the maximum positive back rest position (X2 = +1.414) and the parameter X1 (the shed formation advance) varying between 1.414 and +1.414, the static tension is placed in the 34.11 cN/thread to 47.59 cN/thread interval.

The analysis of the simultaneous influence of the independent parameters shows a 38.06% reduction in static tension (from 76.84 cN/thread at 47.59 cN/thread) while X1 and X2 pass from the negative maximum values to positive maximum values. In the case of the other diagonal, the static tension shall be reduced with 43.7% (from 60.59 cN/yarn at 34.11 cN/yarn) while parameter varies X1 from +1.414 to −1.414 and parameter X2 goes from −1.414 to +1.414.

From the technological point of view, all settings of the X1 and X2 parameters that determine the placement of static tension in the upper half of the experimental field (real values between 35 cN/yarn and 50 cN/yarn) can appreciated as favourable.


Conservation of tensional properties of warp yarns is obtained for the minimum static tension. Therefore the optimum interval can be considered to be - for X1 between 0 and −1.414 and for X2 between +1 and +1.414. In the field considered optimal, the static tension has values between 34 cN/thread and 40 cN/thread. For the warp yarns (breaking force of 620 cN), these values for the static tension values represent 5-6% of their breaking strength.

4. Conclusions

1. The static tension of the warp represents an important technological

parameter for the adjustment of the weaving machine. 2. The level of the warp static tension on the weaving machine is

significantly influenced by the values of the parameters: shed formation advances and the position of back rest in relation to the position of the front rest.

3. The experimental program presented in this paper is a way of finding the settings that provide the minimum values for the static tension.

4. For the conservation of the tensional properties of the warp yarns it is recommended the stationing of the weaving machine in the closed shed position.

REFERENCES

*** Manualul Inginerului Textilist, Vol. 1, Ed. AGIR, Bucureşti (2004).

Cioară I., Tehnologii de Ńesere. Vol. 1, Ed. Performantica, Iaşi (2008). Cioară I., Tehnologii de Ńesere. Vol. 2, Ed. Performantica, Iaşi (2011). Marchiş O., Cioară I., Procese şi maşini de Ńesut fire filamentare şi articole speciale.

Rotaprint IPIaşi (1986). Taloi D., Florian E., Bratu C., Berceanu E., Optimizarea proceselor metalurgice. Ed.

Didactică şi Pedagogică, Bucureşti (1983).

ASPECTE PRIVIND TENSIUNEA STATICĂ A URZELII

PE MAŞINA DE łESUT

(Rezumat)

Tensiunea statică a urzelii reprezintă un parametru tehnologic de bază pentru maşina de Ńesut. Valoarea tensiunii statice se adoptă în concordanŃă cu particularităŃile firelor prelucrate şi particularităŃile Ńesăturilor realizate. În lucrare se prezintă aspecte tehnologice privind modalităŃile de realizare a tensiunii statice a urzelii pe maşina de Ńesut. Sunt analizate influenŃele parametrilor tehnologici (avansul la formarea rostului, denivelarea traversei de spate în raport cu traversa de faŃă) asupra valorii tensiunii statice a urzelii.




COMPRESSION AND BENDING STIFFNESS OF FUNCTIONAL

WEFT KNITTED FABRICS

BY

CRINA BUHAI and MIRELA BLAGA∗∗∗∗



Received: April 15, 2013 Accepted for publication: May 10, 2013

Abstract. This paper presents an investigation on the compression properties and bending stiffness of weft knitted spacer fabrics. The spacer fabrics were manufactured on Stoll CMS 530 E 6.2 computer controlled flat knitting machine. Sixteen kinds of spacer fabrics have been resulted from the combination between different raw materials and four types of the knitted structures. In order to accomplish the physical and psychological comfort requirement of the users, for the face layer, worn next to the skin, was used a soy protein yarn Nm. 56/3 and as spacer yarns and second layer were used synthetic fibres: polyester Nm 30/3, polyamide Nm 50/3 and polypropylene Nm 16. This yarn configuration was used to maintain the body’s microclimate during physical effort or unfavorable climatic conditions.

The KES FB3-AUTO-A compression tester was used for testing the compression property of the spacer fabrics. The testing method was used according to the instruction manual from Kato Tech Co., Ltd and to determine the bending stiffness was used he textile Flexometer.

The results show that fabric structure, thickness, raw material rigidity and the degree of yarn torsion are some parameters with a high influence on the compression and bending stiffness.

The tested mechanical properties were analyzed in accordance to the fabrics parameters: structure, weight, porosity and fabric thickness. Statistical software


44 Crina Buhai and Mirela Blaga

ANOVA and Statistical Regression were used to evaluate the significance of the structural parameters on the compression and bending stiffness properties.

Key words: compression, resilience, spacer weft knitted fabrics, bending stiffness.

1. Introduction

Weft knitted spacer fabrics found a fast development into a large range

of products with applications in all areas of industry. A great attention has been given to weft-knitted spacer fabrics due to

their good transversal compressibility and excellent air permeability. Pereira et al. (2007) analyzed the physical-mechanical properties of some warp knitted fabrics designed for knee braces. The study indicates that in terms of dimensional properties, the knitted spacer fabrics have higher volume and lower bulk density than commercial structures. The researchers discovered that spacer fabrics are more suitable for knee braces than the commercial materials due to the fact that they are thinner and have lower weight. They also find out that the warp knitted spacer fabrics have similar breaking load values on course and wale direction, fact that makes the adequate for fabrics that require a uniform compression level.

Bakhtiari et al. (2006) analyzed the compression properties of the weft knitted fabrics made from shrinkable and non-shrinkable acrylic fibres. The knitted fabrics were produced with different structures and loop lengths. They find out that the fabrics with knit-tuck structure have higher compression rigidity than the knits with missed structures. Also the 20% shrinkable fibres are highly compressible.

Due to the fact that spacer fabrics are able to absorb kinetic mechanical energy under compression actions, Liu et al. (2011), used warp knitted spacer fabrics as a substituent for the polyurethane foams used for cushioning. These fabrics are more suitable for cushioning because of the better moisture transmission, very good compression behavior and similar energy absorption properties with the polyurethane foams.

The good comfort properties of these fabrics recommend them for apparels and medical care (Liu & Hu, 2011). Compression and bending stiffness of the weft knitted spacer fabrics are relevant mechanical properties, especially for functional clothing and cushioning.

Qun Du et al. (2011) studied the bending stiffness of textile fabrics, claiming that aesthetics and handle of textile products mainly depend on bending behavior. They also developed a handle evaluation system based on measuring and characterizing weight, bending, friction and tensile properties of the fabrics.

Ertekin & Marmarali (2012) discovered that the compression resistance of the spacer fabrics produced on circular knitting machines is significantly affected from the spacer yarn type, dial height and surface material.


To summarize, the compression and bending stiffness properties of the spacer fabrics are very important and they are designed according to the processing operations and the end-uses of the knitted fabrics.


The spacer fabrics have endless options regarding the potential yarns combinations and fabrics structures. Due to the fact that the knitted spacer fabrics are designed for functional clothing, for the face layer worn to the skin, was used a soy protein yarn Nm. 56/3 because of its good comfort properties and skin affinity, and as spacer yarns and second layer were used synthetic fibres: polyester Nm 30/3, polyamide Nm 50/3 and polypropylene Nm 16. This yarn configuration was used to maintain the body’s microclimate during physical effort or unfavorable climatic conditions. The spacer fabrics were manufactured using Stoll CMS 530 E 6.2 computer controlled flat knitting machine. Sixteen kinds of spacer fabrics have been resulted from the combination between different raw materials and four types of the knitted structures. Fig. 1 displays the knitting sections of the four spacer structures denoted as S1, S2, S3 and S4.

S1 S2

S3 S4

Fig. 1 − Knitting sections of the spacer structures.


The coding of the samples, the arrangement of yarns in the spacer structure and the fabrics characteristics are shown in Table 1.

Course and wale density per centimeter were measured at five different places on every sample using a magnifying glass and the average values were calculated. Mass per square meter (g/m2) was determined using an electronic balance, KERN ABT 320-4M and the average of ten measured values for each variance was calculated. Thickness of the spacer fabrics was determined using Alambeta instrument. All measurements were repeated five times and Table 1 shows the mean values of the characteristics of the knitted fabrics.

The fabrics porosity was calculated with the eq. 1:

P = (1−m/ρh)*100, [%] (1) where: P represents the fabric porosity, [%]; m – fabric weight, [g/cm2]; ρ – density of the fiber, [g/cm3]; h – fabric thickness, [cm].

Fabric engineering was carried out in order to create an experimental plan, able to performing some comparative analysis. Therefore, the structures S1 and S2 have the same connecting point’s ratio but the structure of the outer layers is different. For structure S3 it can be observed in Table 1 that the number of connection points of the spacer yarn is lower, and the outer layers have knit and tucks in their structure. The structure S4 is formed mostly of missed stitches and the link between the two layers is made using a rib structure.

Table 1

Spacer Fabrics Characteristics

F – Front layer; B – Back layer; S – Spacer yarn

Fabric density Structure of the spacer fabrics Fabric

code F B S

Wales /5cm

Courses /5cm

Weight [g/m2]

Thickness [mm]

Porosity [%]

S1 Soy Soy Soy 33 39 685 3.32 86.41 S1-1 Soy PES PES 33 38 542 2.54 85.17 S1-2 Soy PA PA 33 37 482 2.41 84.49 S1-3 Soy PP PP 33 40 763 4.05 83.61 S2 Soy Soy Soy 33 39 546 3.01 88.06

S2-1 Soy PES PES 30 38 443 2.27 86.42 S2-2 Soy PA PA 32 40 379 2.25 86.91 S2-3 Soy PP PP 33 41 685 3.63 83.57 S3 Soy Soy Soy 34 52 623 3.42 88.01

S3-1 Soy PES PES 34 50 507 2.97 88.13 S3-2 Soy PA PA 36 48 459 2.84 87.46 S3-3 Soy PP PP 34 54 725 3.87 83.70 S4 Soy Soy Soy 42 44 412 2.82 90.38

S4-1 Soy PES PES 42 44 376 2.91 91.13 S4-2 Soy PA PA 44 46 354 2.75 90.60 S4-3 Soy PP PP 42 46 487 3.28 88.39


Statistical software was used to evaluate the experimental data and the analysis of variance (ANOVA) was used to evaluate the significance of fabric structural parameters on the comfort properties of the fabrics. To conclude whether the parameters are significant or not, p values were examined. Ergun (1995) has established that if ‘p” value of one parameter is greater than 0.05, this parameter will not present any influence and it will be ignored.


3.1. Compression Properties of the Spacer Fabrics

The KES FB3-AUTO-A compression tester was used for testing the compression property of the spacer fabrics. The testing method was used according to the instruction manual from Kato Tech Co., Ltd (Kawabata & Niwa, 1996). Five measurements of each 20 cmx20cm size sample were taken under a maximum load of compression of 50 [gf/cm2] and the average values were reported.

The parameters obtained from the compression hysteresis curves are defined in Table 2.

Table 2

The Compresion Properties of Spacer Fabrics

Fabric code

Linearity of compression

Work of compression [gf*cm/cm2]

Resilience of compression

[%]

Thickness at the maximum load

[mm]

S1 0.389 0.955 35.87 2.38

S1-1 0.521 1.040 35.39 1.75

S1-2 0.558 1.765 33.87 1.42

S1-3 0.772 1.057 29.74 3.47

S2 0.362 0.920 38.20 2.11

S2-1 0.544 1.210 36.10 1.13

S2-2 0.585 1.620 35.40 1.27

S2-3 0.725 1.112 31.22 3.02

S3 0.605 1.830 41.30 2.56

S3-1 0.387 1.210 35.74 2.01

S3-2 0.441 1.720 34.40 2.12

S3-3 0.762 1.206 30.70 3.26

S4 0.473 1.622 45.20 1.62

S4-1 0.524 1.674 42.50 1.70

S4-2 0.595 1.923 41.34 1.48

S4-3 0.622 1.470 33.20 2.61


Fig. 2 − Weft knitted spacer fabrics resilience of compression. Analysing the dates from Table 3, one can observe that, the linearity of

compression is increasing with the fabric thickness. The resilience of compression is the percentage energy recovery from the compression deformation in the thickness direction. A higher resilience percentage indicates that the fabric has better recovery property.

From Fig. 2 it can be concluded that the raw material, fabric thickness, density, the arrangement and the connecting distance of the spacer yarn are factors that have a significant influence on the resilience of the spacer fabrics. Thus, structure S4 has the highest resilience and the structure S1 posses the lowest values of the compression resilience. More, the fabrics having both layers made of soy protein yarns have good resilience. By using a synthetic yarn for the reverse layer the resilience will decrease, the lowest values of the recovery it is shown by the fabrics that have the reverse layer made from polypropylene.

Fig. 3 − The relation of resilience of compression and porosity.


The relation between the resilience of compression and the porosity of spacer fabrics it is listed in Fig. 3. It can be noticed that the resilience is increasing with the porosity, so the higher is the porosity; the better is the fabric recovery from compression. The statistical analysis shows that the porosity has a significant effect on the fabrics resilience (p = 0.00035). Also the ANOVA analysis indicates a significant interaction between the raw material and the fabric resilience (p = 0.014) and between the linearity of compression and raw material (p = 0.0032).

3.2. Bending Stiffness of the Spacer Fabrics

Stiffness is the ability of material to resist at deformation. The bending length was determined with the Textile Flexometer as being the length under which the material will bend under an angle of 41º30' (Niculăiasa 2000; Harpa 2003). Samples of 150 x 20 mm dimensions have been weighted, and a number of five measurements of the bending length were determined the average being listed in Table 3.

The bending stiffness was calculated using the formula:

3

2cL

R m =

, [cm] (2)

where: R – bending stiffness, [cm]; m – weight, [g]; Lc – bending length, [cm]

Table 3 Bending Stiffness of Spacer Fabrics

Wale direction Course direction

Fabric code Weight [g]

Bending length [cm]

Bending stiffness

[cm]

Weight [g]

Bending length [cm]

Bending stiffness

[cm]

Fabric bending stiffness

[cm]

S1 2.45 3.75 129.20 2.6 3.53 113.88 121.30 S1-1 1.85 4.20 137.06 2.0 4.01 128.96 132.95 S1-2 1.80 4.26 138.67 1.9 4.10 130.95 134.75 S1-3 2.95 4.36 244.50 2.8 4.14 201.50 221.96 S2 1.75 3.59 80.97 1.8 2.55 29.85 49.16

S2-1 1.65 3.43 66.29 1.7 2.28 20.74 37.08 S2-2 1.35 3.8 74.08 1.6 3.15 50.01 60.87 S2-3 2.50 4.03 163.02 2.4 3.30 84.45 117.33 S3 2.05 3.64 98.87 2.1 3.01 57.27 75.25

S3-1 1.80 3.92 108.01 1.9 3.42 75.67 90.41 S3-2 1.70 4.13 119.32 1.8 3.87 103.93 111.36 S3-3 2.70 4.37 224.55 2.7 3.98 166.44 193.32 S4 1.65 3.33 60.65 1.9 2.47 27.88 41.12

S4-1 1.30 3.47 54.08 1.4 2.70 26.57 37.91 S4-2 1.45 3.62 68.50 1.5 2.45 21.19 38.10 S4-3 2.15 4.08 145.49 2.2 3.44 91.59 115.44


Fig. 4 − The bending stiffness of the weft knitted spacer fabrics.

Fig. 4 outlines the influence of the structure on the bending stiffness of the spacer fabrics. The structure S4 which is formed mostly of miss stitches has the lowest bending stifness, while the structure S1 due to the higher density of the conecting points of the spacer yarn and the density of the outer layers exhibits the highest bending stiffness. The fabrics that have the reverse layer made of polypropilene have the highest values of the bending stiffness due to the yarn rigidity and fabrick thickness.

Fig. 5 − The relationship between bending stiffness and fabric thickness.

Fig. 5 outlines the relationship between bending stiffness and fabric thickness, clearly being that with the increasing of thickness the bending stiffness is higher. The statistical analysis confirm the relationship between the banding stiffness and fabric thickness since the p values is lower than 0.05 (p = 0.007).

However the fabric thickness is not a defining factor for the bending stiffness, the raw material rigidity and the degree of yarn torsion are also very important factors that have a strong influence on this property.


4. Conclusions

In this study, the compression and bending stiffness of weft knitted spacer fabrics designed for functional clothing were investigated, in relationship with yarn type distribution on the layers and fabrics parameters.

The fabric structure, fabric thickness, raw material rigidity and the degree of yarn torsion are some parameters having a high influence on the bending stiffness. The regression statistics demonstrates the influence of thickness on the analysed mechanical properties.

In case of compression properties of the spacer fabrics, from this study it can be concluded that the raw material, fabric thickness, stitch density and the cross section of the fabrics are significant factors. The fabrics having both layers from soy protein yarns show very good resilience. The resilience properties are decreased by using a synthetic yarn for the reverse layer of the spacer fabrics, the lowest values of the recovery it is shown by the fabrics that have the reverse layer made from polypropylene.

Statistical analysis was performed to determine the influence of porosity on the fabrics resilience of compression. ANOVA analysis indicates a significant interaction between the raw material and the fabric resilience and between the linearity of compression and raw material.

Structural design demonstrated a clear influence on the bending stiffness of the spacer fabrics.

Acknowledgments. This paper was financially supported by POSDRU CUANTUMDOC “DOCTORAL STUDIES FOR EUROPEAN PERFORMANCES IN RESEARCH AND INNOVATION” ID79407 project funded by the European Social Fund and Romanian Government.

REFERENCES

Bakhtiari M., Shaikhzadeh Najar S., Etrati S.M., Khorram Toosi Z., Compression

Properties of Weft Knitted Fabrics Consisting of Shrinkable and Non-Shrinkable Acrylic Fibers. Fibers and Polymers, 7, 3, 295 (2006).

Ergun M., SPSS for Windows. Ocak, Ankara, 1995. Ertekin G., Marmarali A., The Compression Characteristics of Weft Knitted Spacer

Fabrics. Tekstil Ve Konfeksiyon, 4, 340 (2012). Harpa R., Metrologie şi controlul calităŃii produselor. Îndrumar de laborator. Ed.

Performantica, Iaşi, 2003. Kawabata S., Niwa M., Modern Textile Characterization Methods. New York, CRC

Press (1996). Liu Y., Hu H. Compression Property and Air Permeability of Weft-Knitted Spacer

Fabrics. Journal of the Textile Institute, 102, 4, 366 (2011). Liu Y., Hu H., Zhao L., Long H., Compression Behavior of Warp-Knitted Spacer Fabrics

for Cushioning Applications. Textile Research Journal, 82, 1, 11 (2011).


Niculăiasa S.M., Studiul comportării materialelor textile la solicitarea de încovoiere. Studiul materialelor textile. Ed. VIE, Iaşi (2000).

Pereira S., Anand S.C., Rajendran S., A Study of the Structure and Properties of Novel Fabrics for Knee Braces. Journal of Industrial Textiles, 36, 4, 279 (2007).

Qun Du Z., Zhou T., Yan N., Hua S., Dong Yu W., Measurement and Characterization of Bending Stiffness for Fabrics. Fibers and Polymers, 12, 1, 104 (2011).

COMPRESIA ŞI RIGIDITATEA LA ÎNCOVOIERE A TRICOTURILOR DIN BĂTĂTURĂ STRATIFICATE

(Rezumat)

Această lucrare prezintă o cercetare asupra proprietăŃilor de compresie şi

rigiditate la încovoiere a tricoturilor din bătătură stratificate. Tricoturile stratificate au fost realizate pe maşina rectilinie electronică de tricotat din bătătură Stoll CMS 530, de fineŃe E 6.2. Şaisprezece variante de tricoturi stratificate au fost obŃinute prin combinarea diferitelor tipuri de materii prime şi a patru variantei de structuri. În vederea îndeplinirii cerinŃelor fizice şi psihologice de confort, pentru stratul faŃă, care vine în contact cu pielea s-a utilizat un fir cu proteine din soia de fineŃe Nm. 56/3, iar ca fire de legatură şi pentru stratul spate s-au folosit fibre sintetice: poliester Nm 30/3, poliamidă Nm 50/3 şi polipropilenă Nm 16. Această aranjare a firelor a fost stabilită pentru a menŃine microclimatul subvestimentar in timpul efortului fizic sau în condiŃii climatice nefavorabile.

Pentru a testa proprietăŃile de compresie ale tricoturilor stratificate s-a folosit aparatul KES FB3-AUTO, în conformitate cu manualul de instrucŃiuni al Kato Tech Co, Ltd, iar pentru a determina rigiditatea la încovoiere s-a utilizat Flexometrul textil.

Rezultatele arată că structura tricotului, grosimea, rigiditatea firului şi torsiunea sunt parametrii care au o influenŃă semnificativă asupra proprietăŃilor de compresie şi rigiditate la încovoiere. ProprietăŃile mecanice testate au fost analizate în corelaŃie cu parametrii de structură, respectiv: structura, masa, porozitatea şi grosimea materialului.

Pentru validarea influenŃei parametrilor de structură asupra proprietăŃilor de compresie şi rigiditatea la încovoiere a tricoturilor stratificate, s-a efectuat analiza statistică şi regresia statistică ANOVA.




3D VIRTUAL MODELING - INNOVATIVE TECHNOLOGY

TO SIMULATE THE CORRESPONDENCE

BETWEEN BODY AND GARMENT

BY

EMILIA FILIPESCU1∗∗∗∗, ELENA SPINACHI

2 and SABINA OLARU

3

1“Gheorghe Asachi” Technical University of Iaşi,

Faculty of Textiles & Leather Engineering and Industrial Management 2SC Gemini CAD Systems SRL, Iaşi

3The National R&D Institute for Textile and Leather, Bucharest


Abstract. In classic clothing design technology, both the manual and CAD

systems, finalizing the design of basic patterns and model requires the production of the prototype, most of times repeating this step until the optimization of the basic and model patterns. This is a laborious task, time consuming and costly.

Research conducted by the authors of this paper focused on improving the design process of customized clothing, through the 3D simulation of the correspondence between the human body and the designed product. Extending the production of clothing according to the real body size of the users is based on the new profile defined for each customer, their desire to purchase a customised product and also the anthropometric survey results that have shown a large variability of the morphological types especially for women.

In the context of globalization of markets and creative industries there is a whole new approach to clothing design process whose ultimate goal it is a new garment engineering that is customer centred. This paper proposes an innovative approach to the clothing design process according to the body size of potential buyers.


54 Emilia Filipescu, Elena Spinachi and Sabina Olaru

Mathematical processing of the raw data allowed the authors to develop an algorithm for the automated design patterns, using the MTM module of the Gemini Pattern Editor software. Patterns made with the actual dimensions of a user have been validated by 3D simulations, using facilities provided by Optitex system.

The paper makes the following contributions to the field of individualized clothing design: morphological characterization of the female body shape by specific indicators necessary for the classification of body types and provided by 3D scanning; development of an algorithm for 2D patterns by using MTM module of the Gemini Pattern Editor software (with application for the dress); 3D virtual simulation of the correspondence between product design and virtual mannequin that correspond to the body dimensions and shape of the tested subject, in order to validate the developed patterns; final reshaping of patterns by re-simulation in the virtual space.

Key words: virtual simulation, garment, human body.

1. Introduction

The widespread use of CAD systems in the apparel industry for models

design, together with the database resulting by 3D scanning technology of the human body are the premises for extending virtual modelling of the body - garment correspondence during the stage of 2D patterns development, based on the specific dimensions of the clients (Da Silveira et al., 2001; Zulch et al., 2011).

In the classic technology of constructive clothing design, basic and model patterns are being completed following the practical execution of the product, a laborious process that involves high costs of labour and raw materials (Simmons & Istook, 2003).

The qualitative leap in the field of industrial design, according to the real dimensions of the customers, the so-called “customized clothing” is currently feasible due the performances of the CAD systems, integration of both modules for MTM and simulation in the virtual environment of the correspondence between body and the product designed in 2D (Jiao & Helander, 2006).

3D simulation of the correspondence between product design and the human body is an innovative technique that improves the whole process of constructive design of clothing products (Jagstam & Klingstam, 2002). This technique has many advantages among which the rapid renewal of models and reducing costs associated with the implementation of prototypes.

In this context, it explains the permanent concern of specialists in the field of constructive designing of clothing to improve the entire process, from defining the initial database to its operation so that the outcome of this process will ensure the users with garments that are correlated with their morphological features.


For this purpose, a methodology is proposed which allow the designer of clothing patterns to use all the facilities offered by the existing CAD systems.

For the implementation of the proposed methodology, the research started from the idea that there are clients with body sizes different from the standard, within limits that can be adapted by the designer to the real shape of the client’s body. For this purpose, the role of the pattern designer is very important from two perspectives:

• Complex characterization for the morphological specifics of the subject’s body, in order to assess the deviations from the standard body;

• Adopting the optimal solution for patterns remodelling during the 3D simulation, interactive technical stage between specialists and CAD system.

In this context, the research objectives were the following: • Elaboration and implementation of the methodology for

morphological characterization of women, an essential step in setting up a scientific database required in the use of innovative simulation techniques of the body-clothing correspondence in cyberspace;

• Application of the methodology to validate the developed patterns for a random body using “virtual fitting”.

In order to fulfil the research objectives, an initial database was created from the anthropometric survey base on 3D scanning of a lot of Romanian adult women. The measurements were performed in 2009.

The initial data of the selection was processed mathematically (one-dimensional statistical method) and compared with the corresponding values given in the literature (SR 13545:2010, SR 13544:2010).

2. Development of Methods for Subjects’ Morphological Analysis

2.1. Mathematical Model for Body Shape Assessing

The production of clothing according to the individual system is very

important for the pattern designer to quickly and correctly evaluate the morphological features of the customer in order to design accurate patterns. In order to fulfil this overall objective, a specific algorithm was developed based on a relatively small number of anthropometric dimensions considered for a certain subject. It allows the pattern designer to quickly and objectively evaluate: body type (standard dimensions) and morphological features - stature, size and conformation for anyone (Filipescu et al., 2009).

The development of the mathematical model required a database for the automated evaluation of morphological features of the tested subjects.

The specifics of a certain body type (size, height group, conformation), and basic morphological indicators (posture, proportions, vertical balance and shoulder position) required the selection of the following anthropometric measurements (Filipescu, 2007):


1. Body height, Ic 2. Bust circumference, Pb 3. Hips circumference, Pş 4. Shoulders length, Lu 5. Thorax length from neck to waist, L’tf 6. Vertical arch of the back, Avs 7. Shoulders inclination angle, α 8. Distance from cervical point to a reference plane, placed behind the

subject, D1 9. Distance from scapula projection to a reference plane, placed behind

the subject, D2 10. Distance from back waist point to a reference plane, placed behind

the subject, D3 11. Distance from buttock point to a reference plane, placed behind the

subject, D4 12. Distance from clavicle point to a reference plane, placed behind the

subject, D5 13. Distance from breast point to a reference plane, placed behind the

subject, D6 14. Distance from the front waist point to a reference plane, placed

behind the subject, D7 15. Distance from the maximum abdomen point to a reference plane,

placed behind the subject, D8. One more step is the acquisition of formation from standard

anthropometric (SR 13545:2010) required to fit the subject to a standardized body type, relating to size groups, heights groups and conformation groups (Table 1).

Table 1

Conformation Groups

Clothing sizes

40 42 44 46 48 50 52 54 56 58 60

Bust circumference Pb

80 84 88 92 96 100 104 110 116 122 128

Confor-mation groups

Pş-Pb

Hips circumference Pş A −4 − − − − − − 100 106 112 118 124 B 0 80 84 88 92 96 100 104 110 116 122 128 C 4 84 88 92 96 100 104 108 114 120 126 132 D 8 88 92 96 100 104 108 112 118 124 130 136 E 12 92 96 100 104 108 112 116 122 128 134 140 F 16 96 100 104 108 112 116 − − − − −

Inter-dimensional range

4 cm 6 cm


The morphological characterization of the subjects involves the calculation of averages and inter-dimensional intervals to assess the following morphological indicators: body stature (Pc), back waist depth (Ats), prominence of buttocks (Pfes), shoulder height (îu), vertical equilibrium (Ev1) and thoracic perimeter (Ipt).

The body stature or body position (Pc, cm) is calculated as the difference between D1 and D2; the back waist depth (first waist depth) Ats, cm is calculated as the difference between D2 and D3 and the buttocks prominence (second waist depth) Pfes, cm is calculated as the difference between D3 and D4. All these three indicators have the following interpretation (Filipescu, 1998):

− Tense stature: Pc < 4.69; Ats < 2.9; Pfes < 3.49 − Normal stature: Pc = 6.2 ± 1.5; Ats = 4.5±1.5; Pfes = 5±1.5 − Crooked stature: Pc > 7.71; Ats > 6.1; Pfes > 6.51. The next morphological indicator, the shoulders height (îu, cm) is

calculated with the following equation:

îu = Lu * sin α (1) Its interpretation is:

− Shoulders lifted, îu < 5.19 − Shoulders in normal position, îu = 5.9± 0.75 − Shoulders descended îu > 6.7. Vertical balance (Ev, cm) is calculated as the difference between the

thorax length from neck to waist (L’tf) and the vertical arch of the back (Avs), offering information about the thorax position:

− Leaned forward, Ev < −0.21 − Normal vertical balance, Ev = 1.8±2 − Leaned back, Ev > 3.81. The thoracic perimeter index (Ipt, %) offers information about the

thorax type and it is calculated by the ratio of bust circumference (Pb) and body height (Ic):

− Narrow thorax, Ipt < 56.9 − Average thorax, Ipt = 60±3 − Large thorax, Ipt = 66±3 − Round thorax, Ipt > 69. The selected anthropometric sizes and morphological indicators were

then used in the two methods of assessing body shape. The mathematical model was developed to assess the overall exterior body shape, but a complex evaluation requires a comparative analysis between the morphological indicators of a subject and the standardized values of the body type that fits the subject in her principal dimensions (body height, bust circumference and hips circumference).


2.2. Complex Evaluation by Comparative Method

Apart from the above mentioned indicators (Pc, Ats and Pfes), the method required the use of several indexes characterizing the body prominence in the frontal plane, on its anterior part. The first additional indicator is the bust prominence (Pbust, cm) which is calculated by the difference between D6 and D5, characterizing the bust type:

− Less prominent bust, Pbust < 9 − Bust with normal prominence, Pbust = 10.5±1.5 − Bust prominent, Pbust > 12.1. The waist depth compared to bust prominence (Atf, cm) is calculated

by the difference between D6 and D7, offering information about the prominence type:

− Waist is more prominent than bust, Atf < 0 − Waist is as prominent as bust, Atf = 0 − Bust is more prominent than waist, Atf > 0. Abdomen prominence compared to bust prominence (Pabd) in cm is

calculated by the difference between D6 and D8, giving information about the prominence type:

− Abdomen is more prominent than bust, Pabd < 0 − Abdomen is as prominent as bust, Pabd = 0 − Bust is more prominent than abdomen, Pabd > 0. The last indicator is the abdomen prominence compared to waist

prominence (Pabd-t) in cm is calculated by the difference between D8 and D7, characterizing the prominence type:

− Abdomen is more prominent than waist, Pabd-t < 0 − Abdomen is as prominent as waist, Pabd-t = 0 − Waist is more prominent than abdomen, Pabd-t > 0.

2.3. Method for Drawing the Body in Sagittal Plane

For a more precise simulation of body-garment correspondence and a

general characterization of the body shape using the two methods described above, the pattern designer needs to visualise shape of the body of the subject.

This visualisation can be obtained by drawing the thorax in the sagittal plane, using a relatively small number of anthropometric sizes, taken from the database from the body scan. If the pattern designer does not have access to the scanned body image and only knows the values of anthropometric measurements resulting from scanning, this visualization is very important.

Drawing the body in a sagittal plane requires the anthropometric sizes specified in Fig. 1.


Fig. 1 – Visualization of the anthropometric body sizes identification.

Knowing the anthropometric measures, the thorax in sagittal plane is drawn in the following sequence:

• In the graphical space a vertical line was drawn, marking all the heights values (anthropometric dimensions no. 1 to 6 in Fig. 1);

• from the waist line height (Ilt), a vertical line was placed (tangent to scapula prominence) that intersects the horizontal line from the cervical point, the resulting segments defining the body posture (Pc) and back waist depth (Ats);

• from the waist line height (Ilt) a vertical line was drawn, parallel to the buttocks the resulting segment being the buttocks prominence (anthropometric dimension no. 9 in Fig. 1);

• an arc is drawn with the scapula prominence point as centre and radius r = D6 − D2 (anterior-posterior bust diameter); the arc will intersect the horizontal line at bust height resulting the anthropometric dimension no. 10 (in Fig. 1);

• a vertical line from the breast point is drawn, and the anthropometric dimensions no. 11 to 14 are defined;

• the contours of the front and back of the torso are drawn.

3. 3D Simulation of Body-Garment Correspondence

The following case study presents the simulation of the body-garment

correspondence, by using the experimental data from morphological researches referring to the feminine body.

For exemplification, a random body was selected from the database (resulting from 3D body scanning), the selection criterion being that conformity


of the subject’s main dimensions to the body type B from the national anthropometric standard - body height of 160 cm, bust circumference of 100 cm and hips circumference of 100 cm (SR 13545:2010). The anthropometric dimensions of the subject were selected from values resulting from scanning.

The case study was conducted according to the methodology developed by using information stored in the database, created for this purpose.

3.1. Morphological Characterization of the Subject

The studied subject exemplifies the fitting for a certain type of stature,

according to the methodology described in paragraph 2.1. In Fig. 2 are presented the values of anthropometric measures necessary for evaluating and classifying the subject according to the body type and to specific morphological indicators, using the developed mathematical model. It is noted according to the posture indicator (Pc) and back waist depth (Ats) the subject has normal posture values.

Fig. 2 – Anthropometric sizes of the subject and her type of stature.

After processing the initial data all information about the subject, as specified in paragraph 2.1 can be obtained. The values show that the subject has a normal posture, flat buttocks, shoulders descend, normal vertical balance and average thorax.

For a more comprehensive characterization of the tested subject, to store information necessary to base pattern design and to ensure the best possible fitting between body and garment, it was used the complex method of assessing the subject’s body shape as specified in paragraph 2.2. Values of the prominence and depths evaluation indicators were compared, on the front and


the rear of the subject with the body type that it fits through the main dimensions taken from standard anthropometric (Standard - SR 13545:2010) results are presented in Table 2.

Table 2

Indicators for Prominence and Depths Assessing Projections for Studied Subject

Evaluation indicator Value according to the anthropometric

standard, [cm]

Experimental value [cm]

Difference [cm]

Body stature (Pc) 6.8 7 −0.2

Back waist depth (Ats) 3.9 3.8 +0.1

Buttocks prominence (Pfes) 5.2 2.9 +2.3

Vertical balance (Ev) 2.5 0.0 +2.5

Bust prominence (Pbust) 10.7 11.4 −0.7

Waist depth compared to bust prominence (Atf)

1.3 −1.4 +2.7

Abdomen prominence compared to bust prominence (Pabd)

0.9 −2.4 +3.3

Abdomen prominence compared to waist prominence (Pabd-t)

0.4 0.5 0.1

Analysing the data from the table above, the following observations can

be made: • the subject has a normal stature (Pc = 7 cm); • bust prominence is comparable to that of the body type; • the subject has flattened buttocks, so a lower buttock prominence

(Pfes) compared with the body type proves that the basin is front-bellied, a specific position for people with prominent abdomen;

• abdomen prominence is more developed than the one of the body type; • waist prominence is also higher than the bust. Morphological analysis of the tested subject by the two proposed

variants provides practical information needed for the pattern designer to remodel the patterns as stage of the 3D simulation process.

Based on the information specified in paragraph 2.3., it is presented in Fig. 3 the concrete values of anthropometric sizes and morphological indicators needed to draw the outline of the thorax in sagittal plan. Also, Fig. 3 presents the obtained drawing of the thorax form and the same body as the 3D scanning result. The results show that the method is useful because it gives the designer additional information on body shape.


Fig. 3 – Visualization of the body by drawing and scanning.

3.2. Simulation in Virtual 3D Cyberspace

Transposing flat forms of clothing patterns using different CAD systems (Lectra, Gemini, Investronica, Gerber, Optitex) in 3D garments is a laborious activity that requires an understanding of the following aspects:

• data regarding the fabrics used for the garment (fibre content, draping, shrinkage, weight etc.);

• the geometry of the body area on which the element/product is positioned;

• the product manufacturing technology; • the possibilities for pattern modification depending on the body shape

and the characteristics of the fabrics. The following information was used in order to solve the simulation of

the body - garment correspondence in static position: • results of the morphological analysis for the subject; • basic pattern design for the dress design using Gemini CAD - design

module Gemini Pattern Editor, for the body type that fits the subject according to the main dimensions (group B of conformation) (Filipescu, 2011);

The transformation of the 2D patterns designed with CAD (eg Gemini CAD – design module Gemini Pattern Editor) to a 3D garment takes place in the following sequence:

• three-dimensional modelling of the mannequin according to the dimensions defined in the dimensional table or the customer’s size;

• import the flat forms (2D) of the patterns from a CAD system; • modelling the patterns surface to obtain the product 3D shape; • check and modify the pattern to ensure the body-garment

correspondence.


The virtual modelling was obtained using the OPTITEX PDS CAD system. The stages of simulation are presented below, exemplifying the results of the first and last stages:

Step 1: Import basic patterns made with MTM Gemini CAD Systems module (for the body type 160-100-100) in the specialized software for the simulation of body-garment correspondence, OPTITEX PDS (Fig. 4).

Fig. 4 – Basic patterns for body type: 160-100-100, group B.

Step 2: Definition of the sewing lines, between the construction of lines

of the two elements, front and back. Step 3: Preparation of the mannequin. Step 4: Positioning of the patterns on the parametric mannequin (Fig. 5).

To obtain the sewing simulation for the garment “dress with semi adjusted silhouette”, patterns should be placed in the PDS work area. The pattern designer has the role to accurately place the patterns to the virtual mannequin from the 3D virtual space. If the placement is not correct, the simulation will not be generated, an error message being displayed. To correctly position the patterns on the virtual mannequin, they must be initially synchronized with the position of the mannequin and then they can be simulated.

Step 5: First simulation stage (Fig. 6). Once the pattern is correctly positioned on the virtual mannequin and the correctness of assembly parts is verified, the simulation stage can begin. The duration of the simulation varies depending on the number of items placed in the window of 3D simulation, the simulation model complexity and the sewing lines.


Fig. 5 – Placing the patterns on parametric mannequin.

Fig. 6 – First simulation stage.

Step 6: Verification of body-garment correspondence (Fig. 7). OPTITEX PDS offers various possibilities to determine the precision of the correspondence between the body and the simulated product, one of them using the stress map. The visualization of stress map offers the pattern designer important information regarding the areas of pattern where he/she must intervene. The fact that the selected subject has a prominent abdomen and a larger thorax length both on front and back sides is shown by the product tension, highlighted in red, as seen in Fig. 7.

Fig. 7 – Virtual correspondence analysis.

Step 7: Modelling the initial pattern according to the subject’s body shape focused on:

• resizing the pattern of the front and back elements on the waistline, with removal of dart on the front element due to abdomen prominence;


• changing the position of upper contour lines on front pattern, because the subject has a front length from the base of neck to the waist larger than the standard value;

• adapting the contour of the front symmetry line to the body particularities (prominent abdomen).

Adapting the basic pattern, developed for the average size of group B conformation to the concrete body form of the tested subject was conducted in successive stages specific for the patterns design activity.

The front pattern requires further processing steps which will define the line termination dart, temporarily built on the side seam contour line (Fig. 8).

Fig. 8 – Successive stages in the modelling of the front element. Step 8: Final evaluation is processed after correcting the basic patterns

according to the initial simulation. The new simulation is obtained after placing the corrected patterns on the virtual mannequin. Fig. 9 shows the correspondence between the mannequin and the dress, based on the modified patterns.

Fig. 9 – New simulation – visualization.


It appears that patterns correction according to the subject’s body particularities ensure a better dimensional fitting between the body shape and the garment.

4. Conclusions

The paper brings a contribution to the development of theoretical and

applied research aimed to improve the construction design process of clothing for concrete subjects, by proving to the experts in this field the performance and innovative techniques of simulation in virtual space of the correspondence between the body and the garment.

The research presented in this paper provides an important contribution to the following topics:

• The morphological analysis of the subjects was carried out using the mathematical model for body characterization, complex comparative analysis, body shape in sagittal view;

• The inventory of dimensional deviations of dimensional indicators between the tested subject and the body type that they fit through the main dimensions;

• The virtual simulation of correspondence between the selected body and garment designed for the body type, with concrete evaluation of unconformities that resulted;

• The development and implementation of solutions in order to adapt the initial base patterns to the concrete form the tested subject, remodelling basic patterns;

• Definition of the final patterns using successive simulation stages so that all stress areas are eliminated.

The research is opportune due to the methodology presented both theoretical and case study form, especially to specialists who carry out their activity in the technical domain of clothing design, both for industry but also for concrete dimensions of potential customers.

REFERENCES

*** Standard - SR 13544:2010 Clothing. Men’s Body Measurement and Garment Sizes.

*** Standard - SR 13545:2010 Clothing. Women’s Body Measurement and Garment

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and Research Directions. International Journal of Production Economics, 72, 1, 1−13 (2001).

Filipescu E. et al., General Aspect Concerning Humanbody Proportion Characterization. Faculty of Textile Engineering Technical University of Liberec and Czech Section of Textile Institute Manchester, STRUTEX (2009).


Filipescu E., Contributions to Individual Clothing 2D and 3D Modeling in Virtual

Space. Ed. Politehnium, Iaşi (2011). Filipescu E., Avadanei M., Structura şi proiectarea confecŃiilor textile. Ed.

Performantica, Iaşi, 67−75 (2007). Filipescu E., Contributions to Optimize Clothing Construction to Ensure

Correspondence Dimensional Body-Clothing System Elements in Static and

Dynamic. Ph. D. Diss., “Gheorghe Asachi” Technical University of Iaşi (1998).

Jagstam M., Klingstam P., A Handbook for Integrating Discrete Event Simulation as an

Aid in Conceptual Design of Manufacturing Systems. In: Proceedings of the 34th Winter Simulation Conference: Exploring New Frontiers, Association for Computing Machinery, New York, 1940–1944 (2002).

Jiao J., Helander M.G., Development of an Electronic Configure-to-Order Platform for

Customized Product Development. Computers in Industry, 57, 231–244 (2006). Simmons K.P, Istook C.L., Body Measurement Technique: Comparing 3D Body

Scanning and Anthropometric Methods for Apparel Applications. Journal of Fashion Marketing and Management, 7, 3, 306−332 (2003).

Zulch G., Koruca H.I., Borkircher M., Simulation-Supported Change Process for

Product Customization – A Case Study in a Garment Company. Computers in Industry, 62, 568–577 (2011).

MODELAREA VIRTUALĂ 3D – TEHNOLOGIE INOVATIVĂ ÎN SIMULAREA VIRTUALĂ A CORESPONDENłEI DINTRE CORP ŞI

PRODUSUL DE ÎMBRĂCĂMINTE

(Rezumat)

În tehnologia clasică de proiectare a îmbrăcămintei, atât în sistem manual cât şi prin folosirea sistemelor CAD, definitivarea procesului de proiectare a tiparelor de bază şi de model necesită execuŃia materială a prototipului, de cele mai multe ori repetarea acestei etape până la definitivarea şi optimizarea tiparelor de bază, respectiv a tiparelor de model. Aceasta este o activitate laborioasă şi se realizează cu un consum mare de timp şi cheltuieli materiale, determinate de execuŃia practică a prototipului.

Cercetările desfăşurate de autorii prezentei lucrări au vizat perfecŃionarea procesului proiectării îmbrăcămintei individualizate, prin simularea în spaŃiul virtual 3D a corespondenŃei dintre corp şi produsul proiectat. Extinderea realizării îmbrăcămintei după dimensiunile corporale concrete ale utilizatorilor are la bază noul profil al acestuia, dorinŃa accentuată de individualizare prin produsul vestimentar pe care îl achiziŃionează dar şi rezultatele anchetelor antropometrice care au demonstrat marea variabilitate a tipurilor morfologice mai ales în cazul femeilor.

În contextul general de globalizare a pieŃelor de desfacere se constată o nouă abordare a întregului proces de proiectare constructivă a îmbrăcămintei al cărei obiectiv final îl reprezintă o nouă inginerie a afacerilor şi anume vânzările centrate pe client. În lucrare se propune o abordare inovativă a procesului proiectării îmbrăcămintei după dimensiunile corporale ale potenŃialilor cumpărători.


Prelucrarea matematică a datelor primare a permis autorilor elaborarea unui algoritm de proiectare a tiparelor în sistem automatizat, prin folosirea modulului MTM din cadrul programului Gemini Pattern Editor. Tiparele realizate, cu dimensiunile concrete ale unui purtător, au fost validate prin simularea 3D, prin utilizarea facilităŃilor oferite de sistemul Optitex.

Lucrarea aduce următoarele contribuŃii la dezvoltarea domeniului de proiectare a îmbrăcămintei individualizate: caracterizarea morfologică a formei corpului la femei prin indicatori specifici oferiti de scanarea 3D, necesari în clasificarea tipurilor de corpuri; elaborarea algoritmului de proiectare 2D a tiparelor, prin folosirea modulului MTM din cadrul programului Gemini Pattern Editor (cu aplicaŃie pentru produsul rochie); simularea în spaŃiul virtual 3D a corespondenŃei dintre produsul proiectat şi corpul virtual care corespunde dimensional şi ca formă cu subiectul testat, în vederea validării tiparelor elaborate; modelarea finală a tiparelor prin resimularea în spaŃiul virtual.




TEXTILE HEATING FABRICS WITH POLYPYRROLE LAYER

BY

DANIELA NEGRU∗∗∗∗ and DORIN AVRAM




Abstract. This paper examines the possibility of obtaining conductive

textile materials with applications in the field of thermal protection. Conductive textiles were made by coating samples of rayon and polyester fabrics with the conductive polymer polypyrrole. Conductive yarns with rubber core wrapped with copper filaments or covered with a layer of silver were inserted into the woven rayon structure. Polyester fabrics coated with polypyrrole have a conductive pattern printed with ink-based fine particles of silver. The samples obtained were analyzed using a thermographic camera, which allows recording the electrical resistance of the sample as well as the temperature emitted by the sample when it is put under electrical voltage. The coating of a thin film of polypyrrole on a cloth in order to obtain heating surfaces present the advantage that is a simple and effective process and at the same time requires a small amount of time; in the process of obtaining the coated fabric, polypyrrole was chosen for its electrical and thermal properties, while the fabric provides elasticity and flexibility of the conductive product.

Key words: heating fabric, polypyrrole, conductive polymer, coated textile.


70 Daniela Negru and Dorin Avram

1. Introduction

By coating textiles with conductive polymers, conductive and

functional textiles can be obtained. These textiles can be used as sensors, actuators, electromagnetic shields, in the field of radar absorption, applications in the heating fabrics field (Bhat et al., 2006). Investigations have been made in the field of heating fabrics made by methods of coating with polymers such as conductive polymers like polypyrrole or with carbon black conductive powders (Smith, 2010; Varesano et al., 2005; Gasana et al., 2006; Dall Aqua et al., 2004; Hakansson et al., 2004).

Methods for obtaining conductive textiles are diverse, some deriving from the textile processes, some being innovative: dyeing-printing of carbon nanotubes in aqueous solution, coating with conductive polymers - polypyrrole, polyaniline, polithiophene, metal fibre yarn, etc.

Requirements for obtaining conductive textiles are: the possibility to integrate electronic components into a textile structure and constant electrical properties, even after repeated washing and wearing.

Electric conductive polymers, described as a new class of “synthetic metals”, have aroused a great interest in recent years. Recent research undertaken in the world shows that conductive polymers are a viable alternative because these can be used in a multitude of applications: electronic devices, luminescent diodes, magnetic screens, actuators. These new materials present a great interest because of the relatively cheap synthesis methods, low consumption of raw materials and electric properties (Kuhn et al., 1995).

The most studied classes of conductive polymers are: polyacetylene, polythiophene, polypyrrole, polyaniline and its derivatives. Numerous methods for transferring the electrical conductivity of these polymers on the flexible textile substrate are based on coating the surface with layers of polymer. Coating is commonly used to provide conductivity for non conductive textile materials, including both natural and synthetic materials. Coated textiles with conductive polymers can be characterized by: measuring their resistivity, electron microscope scanning, properties reflecting thermal behaviour, transmission of electric current over a period of time and power dissipated in the form of thermal energy (heat).

By coating textile substrates with conductive polymers, electrical properties of the polymer can be combined with the strength and flexibility of the substrate fabric. The fragility of the conductive polymer layer does not affect significantly the flexibility and manoeuvrability of coated fabric.

Coated textiles obtained by the oxidative polymerization of the pyrrole monomer on a textile support is a method often used, the factors of influence, in accordance with the literature, being: the thickness of polypyrrole layer, which depends on the quantity of polypyrrole in solution, the oxidant/dopant ratio, the structure of textile materials. Physical and mechanical properties of conductive


textiles can be affected by the doping agents of the monomer, as well as the synthesis parameters, such as time, temperature, pH, and the speed of stirring the solution.

In the present paper the possibility of use electro-conductive textiles for heating purposes is explored, focusing on temperature reached when electrical voltage is applied. The coating of a thin film of polypyrrole on a fabric in order to create heating surfaces presents the advantage of being a simple and effective process and it is not time consuming; for the coated fabric, the polypyrrole was chosen for its electrical and thermal properties, while the fabric provides elasticity and flexibility of the conductive product.


Among other conductive polymers, polypyrrole was considered a

suitable material for coating in textile industry as it presents a good affinity with both natural and chemicals fibres, and the textile substrates can be easily covered by immersion in a solution containing pyrrole, an oxidant and a doping agent. The conductive polymer polypyrrole is often used to produce conductive textiles by chemical polymerization of the pyrrole directly on the textile surface. The polymerization of polypyrrole can be carried out on different substrates, such as textile fibres, yarns, fabrics (Shang et al., 2010; Najar et al., 2007; Lin et al., 2005; Collins & Buckley, 1996).

The following substances were used in the study presented in the paper: − Conductive polymer polypyrrole has been used to coat textile fabrics

in order to obtain homogenous heating surfaces. − Conductive wires are produced by ELEKTRISOLA Feindraht AG,

with rubber core and covered with copper wires (type K306B) and rubber core covered with copper wires coated with a layer of silver (K105 type).

− Pyrrole is purchased from Sigma Aldrich, purity of 98% and the density of 0.967 g/cm3.

− The conductive ink used to print the specific pattern onto the fabric has the trade name Electrodag PF-410 and contains very fine silver particles in a thermoplastic resin.

The method used for the polymerization of the polypyrrole was the oxidative polymerization of the polymer in aqueous solution in the presence of the dopants. Doping is the creation of defects in the structure of the polymer without destroying the polymeric chain. These defects in the polymer may be radicals, anions, cations, or combinations. As mentioned previously, the polypyrrole presents affinity for both natural and chemical fibres; two types of raw materials were selected to produce the fabrics: rayon and polyester. The type of woven fabric used in this research is canvas. The electrical current was distributed in the coated fabric according to a pattern developed by printing with conductive ink or by sewing conductive yarns. Two types of conductive threads


were used: yarns with rubber core wrapped with a copper filament, yarn with rubber core wrapped with a copper filament coated with a layer of silver.

Fig. 1 presents the aspect of the rayon fabrics coated with polypyrrole with a conductive pattern with sewn conductive threads. Since the conductive threads are quite thick and stiff, the smoothness of the fabric surface was obtained by removing some yarns from the warp and weft and in their place were introduced the conductive threads. The electric circuit of the polyester fabrics coated with polypyrrole was produced through ink printing using a special pattern (Fig. 2).

a b

Fig. 1 − Samples of rayon fabrics with conductive threads inserted after polypyrrole coating: with rubber core yarns, wrapped with copper filament coated with silver (a)

and with rubber core yarns wrapped with copper filament (b). The use of an ink path has the following advantages: it can be applied

manually, as well as with printing equipment, the layer thickness varying between 20 and 40 mm. The coated fabric has a good stability, surface resistance being less than 0.025 kΩ/square at a thickness of 25 µm. Additionally, the resistivity is very low, which implies a good conductivity, good flexibility, abrasion resistance and high glass transition temperature.

Fig. 2 − Polypyrrole coated polyester fabric with electrical circuit printed with conductive ink.


The dimensions of the samples with conductive threads inserted after coating with polypyrrole are 50x50 mm. The patterns used for the conductive threads are intended to reduce electrical resistance through an electrical equivalent of resistors connected in parallel (Banaszczyk et al., 2009).


To investigate the effectiveness of heating, the samples were connected

to a source of direct current, and the temperature was measured using a camera IR Termovision AGEMA ® System 900. The experiment was performed at the Department of Textiles at the Ghent University, Belgium. This device is provided with dedicated software to record the hot spots on the surfaces of the samples; the device automatically records the maximum temperature and the temperatures of different points on the samples. Also, it can record electric voltage and amperage. Samples of rayon fabrics coated with polypyrrole were tested in terms to determine their electrical resistance and temperature when an electric voltage is applied. The intensity of the electric current was also recorded. The values obtained for these parameters are presented in Table 1.

Table 1

Electrical Resistance and Maximum Temperature Obtained for Samples of Fabrics of

Rayon Coated with Polypyrrole

Sample Electrical resistance

[kΩ]

I [mA]

Voltage [V]

Temperature [ºC]

Rayon 1(Cu) 33.3 1 30 28.7

Rayon 2(Cu) 8.5 4 34 27

Rayon 3(Cu) 17.5 2 35 29.4

Rayon 4(Cu) 1.76 17 30 44.9

Rayon 5(Cu) 2.13 12 25.5 37

Rayon 6(Ag) 5.2 5 26 31.5

Rayon 7(Ag) 8.5 4 34 38

Rayon 8(Ag) 3.18 11 35 27

For samples of fabrics of rayon coated with polypyrrole with copper

wires in the structure, the maximum temperature reached is 44.9°C for a current


intensity of 17 mA at a voltage of 30 V; for samples of polypyrrole coated rayon fabrics with copper wires covered with silver, the maximum temperature reached is 38°C, at a current of 4 mA and a voltage of 36 V. Dissipated temperature was measured in standard conditions of temperature and relative humidity of the environment (22 ± 2°C and 65 ± 2%).

For the samples of polyester coated with polypyrrole and printed electrical circuit, the values of electrical resistance and temperature are presented in Table 2.

The minimum amount of electrical resistance is 0.23 kΩ, at a voltage of 10 V and the temperature measured on the sample is 44°C. The intensity value recorded is 44 mA. The maximum temperature value obtained for the samples of polyester coated with polypyrrole is 51.6°C under an applied voltage of 30 V.

Table 2

Maximum Temperatures for Different Types of Polyester

Fabrics Coated with Polypyrrole

Sample Electrical

resistance, [kΩ] Intensity

[mA] Voltage

[V] Temperature

[ºC]

PES 1 2 5 10 45.8

PES 2 0.23 44 10 44

PES 3 0.48 21 10 34.3

PES 4 1.3 15 20 37.4

PES 5 2 15 30 51.6

Those values indicate that the samples of polyester coated with

polypyrrole are more advantageous in terms of the energy released as heat. However, the 30 V value applied is quite high, and from this point of view sample PES1 is recommended. Polyester samples coated with polypyrrole have been obtained under the same conditions; the large intervals of the results are influenced by the polymerization process which is a factor that cannot be easily controlled.

Rayon fabrics coated with polypyrrole requires 30 V to heat up to a temperature of 28.7°C, while the maximum temperature reached for polyester fabrics at 30 V is 51.6°C.

4. Conclusions

Heating elements obtained using the presented method can be

incorporated into articles of clothing, such as jackets, pants, gloves, shoes; they can be also used in the heating sound-absorbent systems and blankets, sports equipment, uniforms, helmets, skates and boots, upholstery, etc.


Heating elements that are based on a textile substrate were produced in order to activate different parts of the clothing, thus ensuring the heat needed in the different regions of the body. These items of clothing are supposed to have no additional cables, with the exception of small power units, which can include a battery and optionally a control unit with different temperature levels.

Getting conductive textiles remains an issue opens to specialists and researchers, representing an area of interest in textile research in view of the many applications of these in areas so diverse.

Acknowledgements. The authors want to thank the research staff from the Department of Textiles at the University of Ghent, where conductive textiles were made and tests have been carried out.

REFERENCES

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MATERIALE TEXTILE DE ÎNCĂLZIRE PELICULIZATE CU POLIPIROL

(Rezumat)

Acestă lucrare analizează posibilitatea obŃinerii de materiale textile conductive

cu aplicaŃii în domeniul de încălzire. Materialele textile conductive au fost realizate prin peliculizarea unor mostre de Ńesături de viscoză şi poliester cu polimerul conductiv polipirol. În structura Ńesăturior de viscoză au fost inserate fire conductive cu miez de cauciuc pe care sunt infăşurate filamente de cupru simple sau acoperite cu un strat de argint. Pe Ńesăturile din poliester peliculizate cu polipirol a fost printat un model conductiv cu cerneală pe bază de particule fine de argint. Mostrele obŃinute au fost analizate cu ajutorul unei camere termografice, care permite determinatrea rezistenŃei electrice a mostrei, precum şi înregistrarea temperaturii degajate de aceasta când este pusă sub tensiune electrică.

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